| Directory: | ./ |
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| File: | src/path-planner/states-path-finder.cc |
| Date: | 2025-03-07 11:10:46 |
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| Lines: | 18 | 983 | 1.8% |
| Branches: | 40 | 1954 | 2.0% |
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| 1 | // Copyright (c) 2021, Joseph Mirabel | ||
| 2 | // Authors: Joseph Mirabel (joseph.mirabel@laas.fr), | ||
| 3 | // Florent Lamiraux (florent.lamiraux@laas.fr) | ||
| 4 | // Alexandre Thiault (athiault@laas.fr) | ||
| 5 | // Le Quang Anh (quang-anh.le@laas.fr) | ||
| 6 | // | ||
| 7 | // This file is part of hpp-manipulation. | ||
| 8 | // hpp-manipulation is free software: you can redistribute it | ||
| 9 | // and/or modify it under the terms of the GNU Lesser General Public | ||
| 10 | // License as published by the Free Software Foundation, either version | ||
| 11 | // 3 of the License, or (at your option) any later version. | ||
| 12 | // | ||
| 13 | // hpp-manipulation is distributed in the hope that it will be | ||
| 14 | // useful, but WITHOUT ANY WARRANTY; without even the implied warranty | ||
| 15 | // of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU | ||
| 16 | // General Lesser Public License for more details. You should have | ||
| 17 | // received a copy of the GNU Lesser General Public License along with | ||
| 18 | // hpp-manipulation. If not, see <http://www.gnu.org/licenses/>. | ||
| 19 | |||
| 20 | #include <algorithm> | ||
| 21 | #include <hpp/constraints/affine-function.hh> | ||
| 22 | #include <hpp/constraints/explicit.hh> | ||
| 23 | #include <hpp/constraints/locked-joint.hh> | ||
| 24 | #include <hpp/constraints/solver/by-substitution.hh> | ||
| 25 | #include <hpp/core/collision-validation-report.hh> | ||
| 26 | #include <hpp/core/collision-validation.hh> | ||
| 27 | #include <hpp/core/configuration-shooter.hh> | ||
| 28 | #include <hpp/core/diffusing-planner.hh> | ||
| 29 | #include <hpp/core/path-optimization/random-shortcut.hh> | ||
| 30 | #include <hpp/core/path-planning-failed.hh> | ||
| 31 | #include <hpp/core/path-projector/progressive.hh> | ||
| 32 | #include <hpp/core/path-validation.hh> | ||
| 33 | #include <hpp/core/path-vector.hh> | ||
| 34 | #include <hpp/core/problem-target/goal-configurations.hh> | ||
| 35 | #include <hpp/core/problem-target/task-target.hh> | ||
| 36 | #include <hpp/manipulation/constraint-set.hh> | ||
| 37 | #include <hpp/manipulation/graph/edge.hh> | ||
| 38 | #include <hpp/manipulation/graph/state-selector.hh> | ||
| 39 | #include <hpp/manipulation/graph/state.hh> | ||
| 40 | #include <hpp/manipulation/path-planner/states-path-finder.hh> | ||
| 41 | #include <hpp/manipulation/roadmap.hh> | ||
| 42 | #include <hpp/pinocchio/configuration.hh> | ||
| 43 | #include <hpp/pinocchio/joint-collection.hh> | ||
| 44 | #include <hpp/util/debug.hh> | ||
| 45 | #include <hpp/util/exception-factory.hh> | ||
| 46 | #include <hpp/util/timer.hh> | ||
| 47 | #include <iomanip> | ||
| 48 | #include <map> | ||
| 49 | #include <pinocchio/fwd.hpp> | ||
| 50 | #include <pinocchio/multibody/model.hpp> | ||
| 51 | #include <typeinfo> | ||
| 52 | #include <vector> | ||
| 53 | |||
| 54 | namespace hpp { | ||
| 55 | namespace manipulation { | ||
| 56 | namespace pathPlanner { | ||
| 57 | |||
| 58 | using Eigen::ColBlockIndices; | ||
| 59 | using Eigen::RowBlockIndices; | ||
| 60 | |||
| 61 | using graph::EdgePtr_t; | ||
| 62 | using graph::Edges_t; | ||
| 63 | using graph::LockedJoints_t; | ||
| 64 | using graph::Neighbors_t; | ||
| 65 | using graph::NumericalConstraints_t; | ||
| 66 | using graph::segments_t; | ||
| 67 | using graph::StatePtr_t; | ||
| 68 | using graph::States_t; | ||
| 69 | |||
| 70 | using core::ProblemTargetPtr_t; | ||
| 71 | using core::problemTarget::GoalConfigurations; | ||
| 72 | using core::problemTarget::GoalConfigurationsPtr_t; | ||
| 73 | using core::problemTarget::TaskTarget; | ||
| 74 | using core::problemTarget::TaskTargetPtr_t; | ||
| 75 | |||
| 76 | #ifdef HPP_DEBUG | ||
| 77 | static void displayRoadmap(const core::RoadmapPtr_t& roadmap) { | ||
| 78 | unsigned i = 0; | ||
| 79 | for (auto cc : roadmap->connectedComponents()) { | ||
| 80 | hppDout(info, " CC " << i++); | ||
| 81 | for (auto n : cc->nodes()) { | ||
| 82 | hppDout(info, pinocchio::displayConfig(n->configuration())); | ||
| 83 | } | ||
| 84 | } | ||
| 85 | } | ||
| 86 | #endif | ||
| 87 | |||
| 88 | ✗ | StatesPathFinder::StatesPathFinder(const core::ProblemConstPtr_t& problem, | |
| 89 | ✗ | const core::RoadmapPtr_t& roadmap) | |
| 90 | : PathPlanner(problem, roadmap), | ||
| 91 | ✗ | problem_(HPP_STATIC_PTR_CAST(const manipulation::Problem, problem)), | |
| 92 | ✗ | constraints_(), | |
| 93 | ✗ | index_(), | |
| 94 | ✗ | sameRightHandSide_(), | |
| 95 | ✗ | stricterConstraints_(), | |
| 96 | ✗ | optData_(0x0), | |
| 97 | ✗ | graphData_(0x0), | |
| 98 | ✗ | lastBuiltTransitions_(), | |
| 99 | ✗ | goalConstraints_(), | |
| 100 | ✗ | goalDefinedByConstraints_(false), | |
| 101 | ✗ | q1_(), | |
| 102 | ✗ | q2_(), | |
| 103 | ✗ | configList_(), | |
| 104 | ✗ | idxConfigList_(0), | |
| 105 | ✗ | nTryConfigList_(0), | |
| 106 | ✗ | solved_(false), | |
| 107 | ✗ | interrupt_(false), | |
| 108 | ✗ | weak_() { | |
| 109 | ✗ | gatherGraphConstraints(); | |
| 110 | ✗ | inStateProblem_ = core::Problem::create(problem_->robot()); | |
| 111 | } | ||
| 112 | |||
| 113 | ✗ | StatesPathFinder::StatesPathFinder(const StatesPathFinder& other) | |
| 114 | ✗ | : PathPlanner(other.problem_), | |
| 115 | ✗ | problem_(other.problem_), | |
| 116 | ✗ | constraints_(), | |
| 117 | ✗ | index_(other.index_), | |
| 118 | ✗ | sameRightHandSide_(other.sameRightHandSide_), | |
| 119 | ✗ | weak_() {} | |
| 120 | |||
| 121 | ✗ | StatesPathFinderPtr_t StatesPathFinder::create( | |
| 122 | const core::ProblemConstPtr_t& problem) { | ||
| 123 | StatesPathFinder* ptr; | ||
| 124 | ✗ | RoadmapPtr_t r = Roadmap::create(problem->distance(), problem->robot()); | |
| 125 | try { | ||
| 126 | ✗ | ProblemConstPtr_t p(HPP_DYNAMIC_PTR_CAST(const Problem, problem)); | |
| 127 | ✗ | ptr = new StatesPathFinder(p, r); | |
| 128 | ✗ | } catch (std::exception&) { | |
| 129 | ✗ | throw std::invalid_argument( | |
| 130 | ✗ | "The problem must be of type hpp::manipulation::Problem."); | |
| 131 | } | ||
| 132 | ✗ | StatesPathFinderPtr_t shPtr(ptr); | |
| 133 | ✗ | ptr->init(shPtr); | |
| 134 | ✗ | return shPtr; | |
| 135 | } | ||
| 136 | |||
| 137 | ✗ | StatesPathFinderPtr_t StatesPathFinder::createWithRoadmap( | |
| 138 | const core::ProblemConstPtr_t& problem, const core::RoadmapPtr_t& roadmap) { | ||
| 139 | StatesPathFinder* ptr; | ||
| 140 | ✗ | ProblemConstPtr_t p = HPP_DYNAMIC_PTR_CAST(const Problem, problem); | |
| 141 | ✗ | RoadmapPtr_t r = HPP_DYNAMIC_PTR_CAST(Roadmap, roadmap); | |
| 142 | ✗ | if (!r) | |
| 143 | ✗ | throw std::invalid_argument( | |
| 144 | ✗ | "The roadmap must be of type hpp::manipulation::Roadmap."); | |
| 145 | ✗ | if (!p) | |
| 146 | ✗ | throw std::invalid_argument( | |
| 147 | ✗ | "The problem must be of type hpp::manipulation::Problem."); | |
| 148 | |||
| 149 | ✗ | ptr = new StatesPathFinder(p, r); | |
| 150 | ✗ | StatesPathFinderPtr_t shPtr(ptr); | |
| 151 | ✗ | ptr->init(shPtr); | |
| 152 | ✗ | return shPtr; | |
| 153 | } | ||
| 154 | |||
| 155 | ✗ | StatesPathFinderPtr_t StatesPathFinder::copy() const { | |
| 156 | ✗ | StatesPathFinder* ptr = new StatesPathFinder(*this); | |
| 157 | ✗ | StatesPathFinderPtr_t shPtr(ptr); | |
| 158 | ✗ | ptr->init(shPtr); | |
| 159 | ✗ | return shPtr; | |
| 160 | } | ||
| 161 | |||
| 162 | struct StatesPathFinder::GraphSearchData { | ||
| 163 | StatePtr_t s1; | ||
| 164 | // list of potential goal states | ||
| 165 | // can be multiple if goal is defined as a set of constraints | ||
| 166 | graph::States_t s2; | ||
| 167 | |||
| 168 | // index of the transition list | ||
| 169 | size_t idxSol; | ||
| 170 | |||
| 171 | // Datas for findNextTransitions | ||
| 172 | struct state_with_depth { | ||
| 173 | StatePtr_t s; | ||
| 174 | EdgePtr_t e; | ||
| 175 | std::size_t l; // depth to root | ||
| 176 | std::size_t i; // index in parent state_with_depths | ||
| 177 | // constructor used for root node | ||
| 178 | ✗ | inline state_with_depth() : s(), e(), l(0), i(0) {} | |
| 179 | // constructor used for non-root node | ||
| 180 | ✗ | inline state_with_depth(EdgePtr_t _e, std::size_t _l, std::size_t _i) | |
| 181 | ✗ | : s(_e->stateFrom()), e(_e), l(_l), i(_i) {} | |
| 182 | }; | ||
| 183 | typedef std::vector<state_with_depth> state_with_depths; | ||
| 184 | typedef std::map<StatePtr_t, state_with_depths> StateMap_t; | ||
| 185 | /// std::size_t is the index in state_with_depths at StateMap_t::iterator | ||
| 186 | struct state_with_depth_ptr_t { | ||
| 187 | StateMap_t::iterator state; | ||
| 188 | std::size_t parentIdx; | ||
| 189 | ✗ | state_with_depth_ptr_t(const StateMap_t::iterator& it, std::size_t idx) | |
| 190 | ✗ | : state(it), parentIdx(idx) {} | |
| 191 | }; | ||
| 192 | typedef std::deque<state_with_depth_ptr_t> Deque_t; | ||
| 193 | // vector of pointers to state with depth | ||
| 194 | typedef std::vector<state_with_depth_ptr_t> state_with_depths_t; | ||
| 195 | // transition lists exceeding this depth in the constraint graph will not be | ||
| 196 | // considered | ||
| 197 | std::size_t maxDepth; | ||
| 198 | // map each state X to a list of preceding states in transition lists that | ||
| 199 | // visit X state_with_depth struct gives info to trace the entire transition | ||
| 200 | // lists | ||
| 201 | StateMap_t parent1; | ||
| 202 | // store a vector of pointers to the end state of each transition list | ||
| 203 | state_with_depths_t solutions; | ||
| 204 | // the frontier of the graph search | ||
| 205 | // consists states that have not been expanded on | ||
| 206 | Deque_t queue1; | ||
| 207 | |||
| 208 | // track index of first transition list that has not been checked out | ||
| 209 | // only needed when goal is defined as set of constraints | ||
| 210 | size_t queueIt; | ||
| 211 | |||
| 212 | ✗ | const state_with_depth& getParent(const state_with_depth_ptr_t& _p) const { | |
| 213 | ✗ | const state_with_depths& parents = _p.state->second; | |
| 214 | ✗ | return parents[_p.parentIdx]; | |
| 215 | } | ||
| 216 | |||
| 217 | // add initial state (root node) to the map parent1 | ||
| 218 | ✗ | state_with_depth_ptr_t addInitState() { | |
| 219 | StateMap_t::iterator next = | ||
| 220 | ✗ | parent1.insert(StateMap_t::value_type(s1, state_with_depths(1))).first; | |
| 221 | ✗ | return state_with_depth_ptr_t(next, 0); | |
| 222 | } | ||
| 223 | |||
| 224 | // store a transition to the map parent1 | ||
| 225 | ✗ | state_with_depth_ptr_t addParent(const state_with_depth_ptr_t& _p, | |
| 226 | const EdgePtr_t& transition) { | ||
| 227 | ✗ | const state_with_depths& parents = _p.state->second; | |
| 228 | ✗ | const state_with_depth& from = parents[_p.parentIdx]; | |
| 229 | |||
| 230 | // Insert state to if necessary | ||
| 231 | StateMap_t::iterator next = | ||
| 232 | parent1 | ||
| 233 | ✗ | .insert(StateMap_t::value_type(transition->stateTo(), | |
| 234 | ✗ | state_with_depths())) | |
| 235 | ✗ | .first; | |
| 236 | |||
| 237 | ✗ | next->second.push_back( | |
| 238 | ✗ | state_with_depth(transition, from.l + 1, _p.parentIdx)); | |
| 239 | |||
| 240 | ✗ | return state_with_depth_ptr_t(next, next->second.size() - 1); | |
| 241 | } | ||
| 242 | }; | ||
| 243 | |||
| 244 | ✗ | static bool containsLevelSet(const graph::EdgePtr_t& e) { | |
| 245 | ✗ | graph::WaypointEdgePtr_t we = HPP_DYNAMIC_PTR_CAST(graph::WaypointEdge, e); | |
| 246 | ✗ | if (!we) return false; | |
| 247 | ✗ | for (std::size_t i = 0; i <= we->nbWaypoints(); i++) { | |
| 248 | graph::LevelSetEdgePtr_t lse = | ||
| 249 | ✗ | HPP_DYNAMIC_PTR_CAST(graph::LevelSetEdge, we->waypoint(i)); | |
| 250 | ✗ | if (lse) return true; | |
| 251 | } | ||
| 252 | ✗ | return false; | |
| 253 | } | ||
| 254 | |||
| 255 | ✗ | static bool isLoopTransition(const graph::EdgePtr_t& transition) { | |
| 256 | ✗ | return transition->stateTo() == transition->stateFrom(); | |
| 257 | } | ||
| 258 | |||
| 259 | ✗ | void StatesPathFinder::gatherGraphConstraints() { | |
| 260 | typedef graph::Edge Edge; | ||
| 261 | typedef graph::EdgePtr_t EdgePtr_t; | ||
| 262 | typedef graph::GraphPtr_t GraphPtr_t; | ||
| 263 | typedef constraints::solver::BySubstitution Solver_t; | ||
| 264 | |||
| 265 | ✗ | GraphPtr_t cg(problem_->constraintGraph()); | |
| 266 | ✗ | const ConstraintsAndComplements_t& cac(cg->constraintsAndComplements()); | |
| 267 | ✗ | for (std::size_t i = 0; i < cg->nbComponents(); ++i) { | |
| 268 | ✗ | EdgePtr_t edge(HPP_DYNAMIC_PTR_CAST(Edge, cg->get(i).lock())); | |
| 269 | |||
| 270 | // only gather the edge constraints | ||
| 271 | ✗ | if (!edge) continue; | |
| 272 | |||
| 273 | // Don't even consider level set edges | ||
| 274 | ✗ | if (containsLevelSet(edge)) continue; | |
| 275 | |||
| 276 | ✗ | const Solver_t& solver(edge->pathConstraint()->configProjector()->solver()); | |
| 277 | ✗ | const NumericalConstraints_t& constraints(solver.numericalConstraints()); | |
| 278 | ✗ | for (NumericalConstraints_t::const_iterator it(constraints.begin()); | |
| 279 | ✗ | it != constraints.end(); ++it) { | |
| 280 | // only look at parameterized constraint | ||
| 281 | ✗ | if ((*it)->parameterSize() == 0) continue; | |
| 282 | |||
| 283 | ✗ | const std::string& name((*it)->function().name()); | |
| 284 | // if constraint is in map, no need to add it | ||
| 285 | ✗ | if (index_.find(name) != index_.end()) continue; | |
| 286 | |||
| 287 | ✗ | index_[name] = constraints_.size(); | |
| 288 | // Check whether constraint is equivalent to a previous one | ||
| 289 | ✗ | for (NumericalConstraints_t::const_iterator it1(constraints_.begin()); | |
| 290 | ✗ | it1 != constraints_.end(); ++it1) { | |
| 291 | ✗ | for (ConstraintsAndComplements_t::const_iterator it2(cac.begin()); | |
| 292 | ✗ | it2 != cac.end(); ++it2) { | |
| 293 | ✗ | if (((**it1 == *(it2->complement)) && (**it == *(it2->both))) || | |
| 294 | ✗ | ((**it1 == *(it2->both)) && (**it == *(it2->complement)))) { | |
| 295 | ✗ | assert(sameRightHandSide_.count(*it1) == 0); | |
| 296 | ✗ | assert(sameRightHandSide_.count(*it) == 0); | |
| 297 | ✗ | sameRightHandSide_[*it1] = *it; | |
| 298 | ✗ | sameRightHandSide_[*it] = *it1; | |
| 299 | } | ||
| 300 | } | ||
| 301 | } | ||
| 302 | ✗ | constraints_.push_back(*it); | |
| 303 | hppDout(info, "Adding constraint \"" << name << "\""); | ||
| 304 | hppDout(info, "Edge \"" << edge->name() << "\""); | ||
| 305 | hppDout(info, "parameter size: " << (*it)->parameterSize()); | ||
| 306 | } | ||
| 307 | } | ||
| 308 | // constraint/both is the intersection of both constraint and | ||
| 309 | // constraint/complement | ||
| 310 | ✗ | for (ConstraintsAndComplements_t::const_iterator it(cac.begin()); | |
| 311 | ✗ | it != cac.end(); ++it) { | |
| 312 | ✗ | stricterConstraints_[it->constraint] = it->both; | |
| 313 | ✗ | stricterConstraints_[it->complement] = it->both; | |
| 314 | } | ||
| 315 | } | ||
| 316 | |||
| 317 | ✗ | bool StatesPathFinder::findTransitions(GraphSearchData& d) const { | |
| 318 | // all potential solutions should be attempted before finding more | ||
| 319 | ✗ | if (d.idxSol < d.solutions.size()) return false; | |
| 320 | ✗ | bool done = false; | |
| 321 | ✗ | while (!d.queue1.empty() && !done) { | |
| 322 | ✗ | GraphSearchData::state_with_depth_ptr_t _state = d.queue1.front(); | |
| 323 | |||
| 324 | ✗ | const GraphSearchData::state_with_depth& parent = d.getParent(_state); | |
| 325 | ✗ | if (parent.l >= d.maxDepth) return true; | |
| 326 | ✗ | d.queue1.pop_front(); | |
| 327 | |||
| 328 | ✗ | const Neighbors_t& neighbors = _state.state->first->neighbors(); | |
| 329 | ✗ | for (Neighbors_t::const_iterator _n = neighbors.begin(); | |
| 330 | ✗ | _n != neighbors.end(); ++_n) { | |
| 331 | ✗ | EdgePtr_t transition = _n->second; | |
| 332 | |||
| 333 | // Don't even consider level set edges | ||
| 334 | ✗ | if (containsLevelSet(transition)) continue; | |
| 335 | |||
| 336 | // Avoid identical consecutive transition | ||
| 337 | ✗ | if (transition == parent.e) continue; | |
| 338 | |||
| 339 | // Avoid loop transitions | ||
| 340 | ✗ | if (isLoopTransition(transition)) continue; | |
| 341 | |||
| 342 | // Insert the end state of the new path to parent | ||
| 343 | GraphSearchData::state_with_depth_ptr_t endState = | ||
| 344 | ✗ | d.addParent(_state, transition); | |
| 345 | ✗ | d.queue1.push_back(endState); | |
| 346 | |||
| 347 | // done if last state is one of potential goal states | ||
| 348 | ✗ | if (std::find(d.s2.begin(), d.s2.end(), transition->stateTo()) != | |
| 349 | ✗ | d.s2.end()) { | |
| 350 | ✗ | done = true; | |
| 351 | ✗ | d.solutions.push_back(endState); | |
| 352 | } | ||
| 353 | } | ||
| 354 | } | ||
| 355 | // return true if search is exhausted and goal state not found | ||
| 356 | ✗ | if (!done) return true; | |
| 357 | ✗ | return false; | |
| 358 | } | ||
| 359 | |||
| 360 | ✗ | Edges_t StatesPathFinder::getTransitionList(const GraphSearchData& d, | |
| 361 | const std::size_t& idxSol) const { | ||
| 362 | ✗ | Edges_t transitions; | |
| 363 | ✗ | if (idxSol >= d.solutions.size()) return transitions; | |
| 364 | |||
| 365 | ✗ | const GraphSearchData::state_with_depth_ptr_t endState = d.solutions[idxSol]; | |
| 366 | ✗ | const GraphSearchData::state_with_depth* current = &d.getParent(endState); | |
| 367 | ✗ | transitions.reserve(current->l); | |
| 368 | ✗ | graph::WaypointEdgePtr_t we; | |
| 369 | ✗ | while (current->e) { | |
| 370 | ✗ | assert(current->l > 0); | |
| 371 | ✗ | we = HPP_DYNAMIC_PTR_CAST(graph::WaypointEdge, current->e); | |
| 372 | ✗ | if (we) { | |
| 373 | ✗ | for (int i = (int)we->nbWaypoints(); i >= 0; --i) | |
| 374 | ✗ | transitions.push_back(we->waypoint(i)); | |
| 375 | } else { | ||
| 376 | ✗ | transitions.push_back(current->e); | |
| 377 | } | ||
| 378 | ✗ | current = &d.parent1.at(current->s)[current->i]; | |
| 379 | } | ||
| 380 | ✗ | std::reverse(transitions.begin(), transitions.end()); | |
| 381 | ✗ | return transitions; | |
| 382 | } | ||
| 383 | |||
| 384 | struct StatesPathFinder::OptimizationData { | ||
| 385 | typedef constraints::solver::HierarchicalIterative::Saturation_t Saturation_t; | ||
| 386 | enum RightHandSideStatus_t { | ||
| 387 | // Constraint is not in solver for this waypoint | ||
| 388 | ABSENT, | ||
| 389 | // right hand side of constraint for this waypoint is equal to | ||
| 390 | // right hand side for previous waypoint | ||
| 391 | EQUAL_TO_PREVIOUS, | ||
| 392 | // right hand side of constraint for this waypoint is equal to | ||
| 393 | // right hand side for initial configuration | ||
| 394 | EQUAL_TO_INIT, | ||
| 395 | // right hand side of constraint for this waypoint is equal to | ||
| 396 | // right hand side for goal configuration | ||
| 397 | EQUAL_TO_GOAL | ||
| 398 | }; // enum RightHandSideStatus_t | ||
| 399 | const std::size_t N, nq, nv; | ||
| 400 | std::vector<Solver_t> solvers; | ||
| 401 | std::vector<bool> isTargetWaypoint; | ||
| 402 | // Waypoints lying in each intermediate state | ||
| 403 | matrix_t waypoint; | ||
| 404 | const Configuration_t q1; | ||
| 405 | Configuration_t q2; | ||
| 406 | core::DevicePtr_t robot; | ||
| 407 | // Matrix specifying for each constraint and each waypoint how | ||
| 408 | // the right hand side is initialized in the solver. | ||
| 409 | Eigen::Matrix<LiegroupElement, Eigen::Dynamic, Eigen::Dynamic> M_rhs; | ||
| 410 | Eigen::Matrix<RightHandSideStatus_t, Eigen::Dynamic, Eigen::Dynamic> M_status; | ||
| 411 | // Number of trials to generate each waypoint configuration | ||
| 412 | // _solveGoalConfig: whether we need to solve for goal configuration | ||
| 413 | ✗ | OptimizationData(const core::ProblemConstPtr_t _problem, | |
| 414 | ConfigurationIn_t _q1, ConfigurationIn_t _q2, | ||
| 415 | const Edges_t& transitions, const bool _solveGoalConfig) | ||
| 416 | ✗ | : N(_solveGoalConfig ? transitions.size() : transitions.size() - 1), | |
| 417 | ✗ | nq(_problem->robot()->configSize()), | |
| 418 | ✗ | nv(_problem->robot()->numberDof()), | |
| 419 | ✗ | solvers(N, _problem->robot()->configSpace()), | |
| 420 | ✗ | waypoint(nq, N), | |
| 421 | ✗ | q1(_q1), | |
| 422 | ✗ | robot(_problem->robot()), | |
| 423 | ✗ | M_rhs(), | |
| 424 | ✗ | M_status() { | |
| 425 | ✗ | if (!_solveGoalConfig) { | |
| 426 | ✗ | assert(_q2.size() > 0); | |
| 427 | ✗ | q2 = _q2; | |
| 428 | } | ||
| 429 | ✗ | waypoint.setZero(); | |
| 430 | ✗ | for (auto solver : solvers) { | |
| 431 | // Set maximal number of iterations for each solver | ||
| 432 | ✗ | solver.maxIterations( | |
| 433 | ✗ | _problem->getParameter("StatesPathFinder/maxIteration").intValue()); | |
| 434 | // Set error threshold for each solver | ||
| 435 | ✗ | solver.errorThreshold( | |
| 436 | ✗ | _problem->getParameter("StatesPathFinder/errorThreshold") | |
| 437 | ✗ | .floatValue()); | |
| 438 | } | ||
| 439 | ✗ | assert(transitions.size() > 0); | |
| 440 | ✗ | isTargetWaypoint.assign(transitions.size(), false); | |
| 441 | ✗ | for (std::size_t i = 0; i < transitions.size(); i++) | |
| 442 | ✗ | isTargetWaypoint[i] = transitions[i]->stateTo()->isWaypoint(); | |
| 443 | } | ||
| 444 | }; | ||
| 445 | |||
| 446 | ✗ | bool StatesPathFinder::checkConstantRightHandSide(size_type index) { | |
| 447 | // a goal configuration is required to check if constraint is satisfied | ||
| 448 | // between initial and final configurations | ||
| 449 | ✗ | assert(!goalDefinedByConstraints_); | |
| 450 | ✗ | OptimizationData& d = *optData_; | |
| 451 | ✗ | const ImplicitPtr_t c(constraints_[index]); | |
| 452 | ✗ | LiegroupElement rhsInit(c->function().outputSpace()); | |
| 453 | ✗ | c->rightHandSideFromConfig(d.q1, rhsInit); | |
| 454 | ✗ | LiegroupElement rhsGoal(c->function().outputSpace()); | |
| 455 | ✗ | c->rightHandSideFromConfig(d.q2, rhsGoal); | |
| 456 | // Check that right hand sides are close to each other | ||
| 457 | ✗ | value_type eps(problem_->constraintGraph()->errorThreshold()); | |
| 458 | ✗ | value_type eps2(eps * eps); | |
| 459 | ✗ | if ((rhsGoal - rhsInit).squaredNorm() > eps2) { | |
| 460 | ✗ | return false; | |
| 461 | } | ||
| 462 | // Matrix of solver right hand sides | ||
| 463 | ✗ | for (size_type j = 0; j < d.M_rhs.cols(); ++j) { | |
| 464 | ✗ | d.M_rhs(index, j) = rhsInit; | |
| 465 | } | ||
| 466 | ✗ | return true; | |
| 467 | } | ||
| 468 | |||
| 469 | ✗ | bool StatesPathFinder::checkWaypointRightHandSide(std::size_t ictr, | |
| 470 | std::size_t jslv) const { | ||
| 471 | ✗ | const OptimizationData& d = *optData_; | |
| 472 | ✗ | ImplicitPtr_t c = constraints_[ictr]->copy(); | |
| 473 | ✗ | LiegroupElement rhsNow(c->function().outputSpace()); | |
| 474 | ✗ | assert(rhsNow.size() == c->rightHandSideSize()); | |
| 475 | ✗ | c->rightHandSideFromConfig(d.waypoint.col(jslv), rhsNow); | |
| 476 | ✗ | c = constraints_[ictr]->copy(); | |
| 477 | ✗ | LiegroupElement rhsOther(c->function().outputSpace()); | |
| 478 | ✗ | switch (d.M_status(ictr, jslv)) { | |
| 479 | ✗ | case OptimizationData::EQUAL_TO_INIT: | |
| 480 | ✗ | c->rightHandSideFromConfig(d.q1, rhsOther); | |
| 481 | ✗ | break; | |
| 482 | ✗ | case OptimizationData::EQUAL_TO_GOAL: | |
| 483 | ✗ | assert(!goalDefinedByConstraints_); | |
| 484 | ✗ | c->rightHandSideFromConfig(d.q2, rhsOther); | |
| 485 | ✗ | break; | |
| 486 | ✗ | case OptimizationData::EQUAL_TO_PREVIOUS: | |
| 487 | ✗ | c->rightHandSideFromConfig(d.waypoint.col(jslv - 1), rhsOther); | |
| 488 | ✗ | break; | |
| 489 | ✗ | case OptimizationData::ABSENT: | |
| 490 | default: | ||
| 491 | ✗ | return true; | |
| 492 | } | ||
| 493 | ✗ | hpp::pinocchio::vector_t diff = rhsOther - rhsNow; | |
| 494 | hpp::pinocchio::vector_t diffmask = | ||
| 495 | ✗ | hpp::pinocchio::vector_t::Zero(diff.size()); | |
| 496 | ✗ | for (auto k : c->activeRows()) // filter with constraint mask | |
| 497 | ✗ | for (size_type kk = k.first; kk < k.first + k.second; kk++) | |
| 498 | ✗ | diffmask[kk] = diff[kk]; | |
| 499 | ✗ | value_type eps(problem_->constraintGraph()->errorThreshold()); | |
| 500 | ✗ | value_type eps2(eps * eps); | |
| 501 | ✗ | return diffmask.squaredNorm() < eps2; | |
| 502 | } | ||
| 503 | |||
| 504 | ✗ | bool StatesPathFinder::checkWaypointRightHandSide(std::size_t jslv) const { | |
| 505 | ✗ | for (std::size_t ictr = 0; ictr < constraints_.size(); ictr++) | |
| 506 | ✗ | if (!checkWaypointRightHandSide(ictr, jslv)) return false; | |
| 507 | ✗ | return true; | |
| 508 | } | ||
| 509 | |||
| 510 | ✗ | void StatesPathFinder::displayRhsMatrix() { | |
| 511 | ✗ | OptimizationData& d = *optData_; | |
| 512 | ✗ | Eigen::Matrix<LiegroupElement, Eigen::Dynamic, Eigen::Dynamic>& m = d.M_rhs; | |
| 513 | |||
| 514 | ✗ | for (std::size_t i = 0; i < constraints_.size(); i++) { | |
| 515 | ✗ | const ImplicitPtr_t& constraint = constraints_[i]; | |
| 516 | ✗ | for (std::size_t j = 0; j < d.solvers.size(); j++) { | |
| 517 | ✗ | const vectorIn_t& config = d.waypoint.col(j); | |
| 518 | ✗ | LiegroupElement le(constraint->function().outputSpace()); | |
| 519 | ✗ | constraint->rightHandSideFromConfig(d.waypoint.col(j), le); | |
| 520 | ✗ | m(i, j) = le; | |
| 521 | } | ||
| 522 | } | ||
| 523 | |||
| 524 | ✗ | std::ostringstream oss; | |
| 525 | ✗ | oss.precision(2); | |
| 526 | ✗ | oss << "\\documentclass[12pt,landscape]{article}" << std::endl; | |
| 527 | ✗ | oss << "\\usepackage[a3paper]{geometry}" << std::endl; | |
| 528 | ✗ | oss << "\\begin {document}" << std::endl; | |
| 529 | |||
| 530 | ✗ | for (size_type ii = 0; ii < (m.cols() + 7) / 8; ii++) { | |
| 531 | ✗ | size_type j0 = ii * 8; | |
| 532 | ✗ | size_type j1 = std::min(ii * 8 + 8, m.cols()); | |
| 533 | ✗ | size_type dj = j1 - j0; | |
| 534 | ✗ | oss << "\\begin {tabular}{"; | |
| 535 | ✗ | for (size_type j = 0; j < dj + 2; ++j) oss << "c"; | |
| 536 | ✗ | oss << "}" << std::endl; | |
| 537 | ✗ | oss << "Constraint & mask"; | |
| 538 | ✗ | for (size_type j = j0; j < j1; ++j) oss << " & WP" << j; | |
| 539 | ✗ | oss << "\\\\" << std::endl; | |
| 540 | ✗ | for (size_type i = 0; i < m.rows(); ++i) { | |
| 541 | ✗ | std::vector<int> mask(constraints_[i]->parameterSize()); | |
| 542 | ✗ | for (auto k : constraints_[i]->activeRows()) | |
| 543 | ✗ | for (size_type kk = k.first; kk < k.first + k.second; kk++) | |
| 544 | ✗ | mask[kk] = 1; | |
| 545 | ✗ | std::ostringstream oss1; | |
| 546 | ✗ | oss1.precision(2); | |
| 547 | ✗ | std::ostringstream oss2; | |
| 548 | ✗ | oss2.precision(2); | |
| 549 | ✗ | oss1 << constraints_[i]->function().name() << " & "; | |
| 550 | |||
| 551 | ✗ | oss1 << "$\\left(\\begin{array}{c} "; | |
| 552 | ✗ | for (std::size_t k = 0; k < mask.size(); ++k) { | |
| 553 | ✗ | oss1 << mask[k] << "\\\\ "; | |
| 554 | } | ||
| 555 | ✗ | oss1 << "\\end{array}\\right)$" << std::endl; | |
| 556 | ✗ | oss1 << " & " << std::endl; | |
| 557 | |||
| 558 | ✗ | for (size_type j = j0; j < j1; ++j) { | |
| 559 | ✗ | if (d.M_status(i, j) != OptimizationData::ABSENT || | |
| 560 | ✗ | (j < m.cols() - 1 && | |
| 561 | ✗ | d.M_status(i, j + 1) == OptimizationData::EQUAL_TO_PREVIOUS)) { | |
| 562 | ✗ | oss2 << "$\\left(\\begin{array}{c} "; | |
| 563 | ✗ | for (size_type k = 0; k < m(i, j).size(); ++k) { | |
| 564 | ✗ | oss2 << ((abs(m(i, j).vector()[k]) < 1e-6) ? 0 | |
| 565 | ✗ | : m(i, j).vector()[k]) | |
| 566 | ✗ | << "\\\\ "; | |
| 567 | } | ||
| 568 | ✗ | oss2 << "\\end{array}\\right)$" << std::endl; | |
| 569 | } | ||
| 570 | ✗ | if (j < j1 - 1) { | |
| 571 | ✗ | oss2 << " & " << std::endl; | |
| 572 | } | ||
| 573 | } | ||
| 574 | ✗ | std::string str2 = oss2.str(); | |
| 575 | ✗ | if (str2.size() > 50) { // don't display constraints used nowhere | |
| 576 | ✗ | oss << oss1.str() << str2 << "\\\\" << std::endl; | |
| 577 | } | ||
| 578 | } | ||
| 579 | ✗ | oss << "\\end{tabular}" << std::endl << std::endl; | |
| 580 | } | ||
| 581 | ✗ | oss << "\\end{document}" << std::endl; | |
| 582 | |||
| 583 | ✗ | std::string s = oss.str(); | |
| 584 | ✗ | std::string s2 = ""; | |
| 585 | ✗ | for (std::size_t i = 0; i < s.size(); i++) { | |
| 586 | ✗ | if (s[i] == '_') | |
| 587 | ✗ | s2 += "\\_"; | |
| 588 | else | ||
| 589 | ✗ | s2.push_back(s[i]); | |
| 590 | } | ||
| 591 | hppDout(info, s2); | ||
| 592 | } | ||
| 593 | |||
| 594 | ✗ | void StatesPathFinder::displayStatusMatrix(const graph::Edges_t& transitions) { | |
| 595 | const Eigen::Matrix<OptimizationData::RightHandSideStatus_t, Eigen::Dynamic, | ||
| 596 | ✗ | Eigen::Dynamic>& m = optData_->M_status; | |
| 597 | ✗ | std::ostringstream oss; | |
| 598 | ✗ | oss.precision(5); | |
| 599 | ✗ | oss << "\\documentclass[12pt,landscape]{article}" << std::endl; | |
| 600 | ✗ | oss << "\\usepackage[a3paper]{geometry}" << std::endl; | |
| 601 | ✗ | oss << "\\begin {document}" << std::endl; | |
| 602 | ✗ | oss << "\\paragraph{Edges}" << std::endl; | |
| 603 | ✗ | oss << "\\begin{enumerate}" << std::endl; | |
| 604 | ✗ | for (auto edge : transitions) { | |
| 605 | ✗ | oss << "\\item \\texttt{" << edge->name() << "}" << std::endl; | |
| 606 | } | ||
| 607 | ✗ | oss << "\\end{enumerate}" << std::endl; | |
| 608 | ✗ | oss << "\\begin {tabular}{l|"; | |
| 609 | ✗ | for (size_type j = 0; j < m.cols(); ++j) | |
| 610 | ✗ | if (transitions[j]->stateTo()->isWaypoint()) | |
| 611 | ✗ | oss << "c"; | |
| 612 | else | ||
| 613 | ✗ | oss << "|c|"; | |
| 614 | ✗ | oss << "|}" << std::endl; | |
| 615 | ✗ | oss << "Constraint"; | |
| 616 | ✗ | for (size_type j = 0; j < m.cols(); ++j) oss << " & " << j + 1; | |
| 617 | ✗ | oss << "\\\\" << std::endl; | |
| 618 | ✗ | for (size_type i = 0; i < m.rows(); ++i) { | |
| 619 | ✗ | oss << "\\texttt{" << constraints_[i]->function().name() << "} & " | |
| 620 | ✗ | << std::endl; | |
| 621 | ✗ | for (size_type j = 0; j < m.cols(); ++j) { | |
| 622 | ✗ | oss << m(i, j); | |
| 623 | ✗ | if (j < m.cols() - 1) oss << " & "; | |
| 624 | } | ||
| 625 | ✗ | oss << "\\\\" << std::endl; | |
| 626 | } | ||
| 627 | ✗ | oss << "\\end{tabular}" << std::endl; | |
| 628 | ✗ | oss << "\\end{document}" << std::endl; | |
| 629 | |||
| 630 | ✗ | std::string s = oss.str(); | |
| 631 | ✗ | std::string s2 = ""; | |
| 632 | ✗ | for (std::size_t i = 0; i < s.size(); i++) { | |
| 633 | ✗ | if (s[i] == '_') | |
| 634 | ✗ | s2 += "\\_"; | |
| 635 | else | ||
| 636 | ✗ | s2.push_back(s[i]); | |
| 637 | } | ||
| 638 | hppDout(info, s2); | ||
| 639 | } | ||
| 640 | |||
| 641 | ✗ | bool StatesPathFinder::contains(const Solver_t& solver, | |
| 642 | const ImplicitPtr_t& c) const { | ||
| 643 | ✗ | if (solver.contains(c)) return true; | |
| 644 | std::map<ImplicitPtr_t, ImplicitPtr_t>::const_iterator it( | ||
| 645 | ✗ | sameRightHandSide_.find(c)); | |
| 646 | ✗ | if (it != sameRightHandSide_.end() && solver.contains(it->second)) | |
| 647 | ✗ | return true; | |
| 648 | ✗ | return false; | |
| 649 | } | ||
| 650 | |||
| 651 | ✗ | bool StatesPathFinder::containsStricter(const Solver_t& solver, | |
| 652 | const ImplicitPtr_t& c) const { | ||
| 653 | ✗ | if (solver.contains(c)) return true; | |
| 654 | std::map<ImplicitPtr_t, ImplicitPtr_t>::const_iterator it( | ||
| 655 | ✗ | stricterConstraints_.find(c)); | |
| 656 | ✗ | if (it != stricterConstraints_.end() && solver.contains(it->second)) | |
| 657 | ✗ | return true; | |
| 658 | ✗ | return false; | |
| 659 | } | ||
| 660 | |||
| 661 | ✗ | bool StatesPathFinder::buildOptimizationProblem( | |
| 662 | const graph::Edges_t& transitions) { | ||
| 663 | ✗ | OptimizationData& d = *optData_; | |
| 664 | // if no waypoint, check init and goal has same RHS | ||
| 665 | ✗ | if (d.N == 0) { | |
| 666 | ✗ | assert(transitions.size() == 1); | |
| 667 | ✗ | assert(!goalDefinedByConstraints_); | |
| 668 | ✗ | size_type index = 0; | |
| 669 | ✗ | for (NumericalConstraints_t::const_iterator it(constraints_.begin()); | |
| 670 | ✗ | it != constraints_.end(); ++it, ++index) { | |
| 671 | ✗ | const ImplicitPtr_t& c(*it); | |
| 672 | // Get transition solver | ||
| 673 | const Solver_t& trSolver( | ||
| 674 | ✗ | transitions[0]->pathConstraint()->configProjector()->solver()); | |
| 675 | ✗ | if (!contains(trSolver, c)) continue; | |
| 676 | ✗ | if (!checkConstantRightHandSide(index)) return false; | |
| 677 | } | ||
| 678 | ✗ | return true; | |
| 679 | } | ||
| 680 | ✗ | d.M_status.resize(constraints_.size(), d.N); | |
| 681 | ✗ | d.M_status.fill(OptimizationData::ABSENT); | |
| 682 | ✗ | d.M_rhs.resize(constraints_.size(), d.N); | |
| 683 | ✗ | d.M_rhs.fill(LiegroupElement()); | |
| 684 | ✗ | size_type index = 0; | |
| 685 | // Loop over constraints | ||
| 686 | ✗ | for (NumericalConstraints_t::const_iterator it(constraints_.begin()); | |
| 687 | ✗ | it != constraints_.end(); ++it, ++index) { | |
| 688 | ✗ | const ImplicitPtr_t& c(*it); | |
| 689 | // Loop forward over waypoints to determine right hand sides equal | ||
| 690 | // to initial configuration or previous configuration | ||
| 691 | ✗ | for (std::size_t j = 0; j < d.N; ++j) { | |
| 692 | // Get transition solver | ||
| 693 | const Solver_t& trSolver( | ||
| 694 | ✗ | transitions[j]->pathConstraint()->configProjector()->solver()); | |
| 695 | ✗ | if (!contains(trSolver, c)) continue; | |
| 696 | |||
| 697 | ✗ | if ((j == 0) || | |
| 698 | ✗ | d.M_status(index, j - 1) == OptimizationData::EQUAL_TO_INIT) { | |
| 699 | ✗ | d.M_status(index, j) = OptimizationData::EQUAL_TO_INIT; | |
| 700 | } else { | ||
| 701 | ✗ | d.M_status(index, j) = OptimizationData::EQUAL_TO_PREVIOUS; | |
| 702 | } | ||
| 703 | } | ||
| 704 | // If the goal configuration is not given | ||
| 705 | // no need to determine if RHS equal to goal configuration | ||
| 706 | ✗ | if (goalDefinedByConstraints_) { | |
| 707 | ✗ | continue; | |
| 708 | } | ||
| 709 | // Loop backward over waypoints to determine right hand sides equal | ||
| 710 | // to final configuration | ||
| 711 | ✗ | for (size_type j = d.N - 1; j > 0; --j) { | |
| 712 | // Get transition solver | ||
| 713 | ✗ | const Solver_t& trSolver(transitions[(std::size_t)j + 1] | |
| 714 | ✗ | ->pathConstraint() | |
| 715 | ✗ | ->configProjector() | |
| 716 | ✗ | ->solver()); | |
| 717 | ✗ | if (!contains(trSolver, c)) break; | |
| 718 | |||
| 719 | ✗ | if ((j == (size_type)d.N - 1) || | |
| 720 | ✗ | d.M_status(index, j + 1) == OptimizationData::EQUAL_TO_GOAL) { | |
| 721 | // if constraint right hand side is already equal to | ||
| 722 | // initial config, check that right hand side is equal | ||
| 723 | // for init and goal configs. | ||
| 724 | ✗ | if (d.M_status(index, j) == OptimizationData::EQUAL_TO_INIT) { | |
| 725 | ✗ | if (checkConstantRightHandSide(index)) { | |
| 726 | // stop for this constraint | ||
| 727 | ✗ | break; | |
| 728 | } else { | ||
| 729 | // Right hand side of constraint should be equal along the | ||
| 730 | // whole path but is different at init and at goal configs. | ||
| 731 | ✗ | return false; | |
| 732 | } | ||
| 733 | } else { | ||
| 734 | ✗ | d.M_status(index, j) = OptimizationData::EQUAL_TO_GOAL; | |
| 735 | } | ||
| 736 | } | ||
| 737 | } | ||
| 738 | } // for (NumericalConstraints_t::const_iterator it | ||
| 739 | #ifdef HPP_DEBUG | ||
| 740 | displayStatusMatrix(transitions); | ||
| 741 | #endif | ||
| 742 | // Fill solvers with target constraints of transition | ||
| 743 | ✗ | for (std::size_t j = 0; j < d.N; ++j) { | |
| 744 | ✗ | d.solvers[j] = | |
| 745 | ✗ | transitions[j]->targetConstraint()->configProjector()->solver(); | |
| 746 | ✗ | if (goalDefinedByConstraints_) { | |
| 747 | ✗ | continue; | |
| 748 | } | ||
| 749 | // when goal configuration is given, and if something | ||
| 750 | // (eg relative pose of two objects grasping) is fixed until goal, | ||
| 751 | // we need to propagate the constraint to an earlier solver, | ||
| 752 | // otherwise the chance it solves for the correct config is very low | ||
| 753 | ✗ | if (j > 0 && j < d.N - 1) { | |
| 754 | const Solver_t& otherSolver = | ||
| 755 | ✗ | transitions[j + 1]->pathConstraint()->configProjector()->solver(); | |
| 756 | ✗ | for (std::size_t i = 0; i < constraints_.size(); i++) { | |
| 757 | // transition from j-1 to j does not contain this constraint | ||
| 758 | // transition from j to j+1 (all the way to goal) has constraint | ||
| 759 | // constraint must be added to solve for waypoint at j (WP_j+1) | ||
| 760 | ✗ | if (d.M_status(i, j - 1) == OptimizationData::ABSENT && | |
| 761 | ✗ | d.M_status(i, j) == OptimizationData::EQUAL_TO_GOAL && | |
| 762 | ✗ | !contains(d.solvers[j], constraints_[i]) && | |
| 763 | ✗ | otherSolver.contains(constraints_[i])) { | |
| 764 | ✗ | d.solvers[j].add(constraints_[i]); | |
| 765 | hppDout(info, "Adding missing constraint " | ||
| 766 | << constraints_[i]->function().name() | ||
| 767 | << " to solver for waypoint" << j + 1); | ||
| 768 | } | ||
| 769 | } | ||
| 770 | } | ||
| 771 | } | ||
| 772 | |||
| 773 | // if goal is defined by constraints, some goal constraints may be | ||
| 774 | // missing from the end state. we should add these constraints to solver | ||
| 775 | // for the config in the final state | ||
| 776 | ✗ | if (goalDefinedByConstraints_) { | |
| 777 | ✗ | for (auto goalConstraint : goalConstraints_) { | |
| 778 | ✗ | if (!containsStricter(d.solvers[d.N - 1], goalConstraint)) { | |
| 779 | ✗ | d.solvers[d.N - 1].add(goalConstraint); | |
| 780 | hppDout(info, "Adding goal constraint " | ||
| 781 | << goalConstraint->function().name() | ||
| 782 | << " to solver for waypoint" << d.N); | ||
| 783 | } | ||
| 784 | } | ||
| 785 | } | ||
| 786 | |||
| 787 | ✗ | return true; | |
| 788 | } | ||
| 789 | |||
| 790 | ✗ | bool StatesPathFinder::checkSolverRightHandSide(std::size_t ictr, | |
| 791 | std::size_t jslv) const { | ||
| 792 | ✗ | const OptimizationData& d = *optData_; | |
| 793 | ✗ | ImplicitPtr_t c = constraints_[ictr]->copy(); | |
| 794 | ✗ | const Solver_t& solver = d.solvers[jslv]; | |
| 795 | ✗ | vector_t rhs(c->rightHandSideSize()); | |
| 796 | ✗ | solver.getRightHandSide(c, rhs); | |
| 797 | ✗ | LiegroupElement rhsNow(c->function().outputSpace()); | |
| 798 | ✗ | assert(rhsNow.size() == rhs.size()); | |
| 799 | ✗ | rhsNow.vector() = rhs; | |
| 800 | ✗ | LiegroupElement rhsOther(c->function().outputSpace()); | |
| 801 | ✗ | switch (d.M_status(ictr, jslv)) { | |
| 802 | ✗ | case OptimizationData::EQUAL_TO_INIT: | |
| 803 | ✗ | c->rightHandSideFromConfig(d.q1, rhsOther); | |
| 804 | ✗ | break; | |
| 805 | ✗ | case OptimizationData::EQUAL_TO_GOAL: | |
| 806 | ✗ | assert(!goalDefinedByConstraints_); | |
| 807 | ✗ | c->rightHandSideFromConfig(d.q2, rhsOther); | |
| 808 | ✗ | break; | |
| 809 | ✗ | case OptimizationData::EQUAL_TO_PREVIOUS: | |
| 810 | ✗ | c->rightHandSideFromConfig(d.waypoint.col(jslv - 1), rhsOther); | |
| 811 | ✗ | break; | |
| 812 | ✗ | case OptimizationData::ABSENT: | |
| 813 | default: | ||
| 814 | ✗ | return true; | |
| 815 | } | ||
| 816 | ✗ | hpp::pinocchio::vector_t diff = rhsOther - rhsNow; | |
| 817 | hpp::pinocchio::vector_t diffmask = | ||
| 818 | ✗ | hpp::pinocchio::vector_t::Zero(diff.size()); | |
| 819 | ✗ | for (auto k : c->activeRows()) // filter with constraint mask | |
| 820 | ✗ | for (size_type kk = k.first; kk < k.first + k.second; kk++) | |
| 821 | ✗ | diffmask[kk] = diff[kk]; | |
| 822 | ✗ | value_type eps(problem_->constraintGraph()->errorThreshold()); | |
| 823 | ✗ | value_type eps2(eps * eps); | |
| 824 | ✗ | if (diffmask.squaredNorm() > eps2) | |
| 825 | hppDout(warning, diffmask.squaredNorm() << " vs " << eps2); | ||
| 826 | ✗ | return diffmask.squaredNorm() < eps2; | |
| 827 | } | ||
| 828 | |||
| 829 | ✗ | bool StatesPathFinder::checkSolverRightHandSide(std::size_t jslv) const { | |
| 830 | ✗ | for (std::size_t ictr = 0; ictr < constraints_.size(); ictr++) | |
| 831 | ✗ | if (!checkSolverRightHandSide(ictr, jslv)) return false; | |
| 832 | ✗ | return true; | |
| 833 | } | ||
| 834 | |||
| 835 | ✗ | bool StatesPathFinder::buildOptimizationProblemFromNames( | |
| 836 | std::vector<std::string> names) { | ||
| 837 | ✗ | graph::Edges_t transitions; | |
| 838 | ✗ | graph::GraphPtr_t cg(problem_->constraintGraph()); | |
| 839 | ✗ | for (const std::string& name : names) { | |
| 840 | ✗ | for (std::size_t i = 0; i < cg->nbComponents(); ++i) { | |
| 841 | graph::EdgePtr_t edge( | ||
| 842 | ✗ | HPP_DYNAMIC_PTR_CAST(graph::Edge, cg->get(i).lock())); | |
| 843 | ✗ | if (edge && edge->name() == name) transitions.push_back(edge); | |
| 844 | } | ||
| 845 | } | ||
| 846 | ✗ | return buildOptimizationProblem(transitions); | |
| 847 | } | ||
| 848 | |||
| 849 | ✗ | void StatesPathFinder::preInitializeRHS(std::size_t j, Configuration_t& q) { | |
| 850 | ✗ | OptimizationData& d = *optData_; | |
| 851 | ✗ | Solver_t& solver(d.solvers[j]); | |
| 852 | ✗ | for (std::size_t i = 0; i < constraints_.size(); ++i) { | |
| 853 | ✗ | const ImplicitPtr_t& c(constraints_[i]); | |
| 854 | ✗ | bool ok = true; | |
| 855 | ✗ | switch (d.M_status((size_type)i, (size_type)j)) { | |
| 856 | ✗ | case OptimizationData::EQUAL_TO_INIT: | |
| 857 | ✗ | ok = solver.rightHandSideFromConfig(c, d.q1); | |
| 858 | ✗ | break; | |
| 859 | ✗ | case OptimizationData::EQUAL_TO_GOAL: | |
| 860 | ✗ | assert(!goalDefinedByConstraints_); | |
| 861 | ✗ | ok = solver.rightHandSideFromConfig(c, d.q2); | |
| 862 | ✗ | break; | |
| 863 | ✗ | case OptimizationData::EQUAL_TO_PREVIOUS: | |
| 864 | ✗ | ok = solver.rightHandSideFromConfig(c, q); | |
| 865 | ✗ | break; | |
| 866 | ✗ | case OptimizationData::ABSENT: | |
| 867 | default:; | ||
| 868 | } | ||
| 869 | ✗ | ok |= contains(solver, constraints_[i]); | |
| 870 | ✗ | if (!ok) { | |
| 871 | ✗ | std::ostringstream err_msg; | |
| 872 | ✗ | err_msg << "\nConstraint " << i << " missing for waypoint " << j + 1 | |
| 873 | ✗ | << " (" << c->function().name() << ")\n" | |
| 874 | ✗ | << "The constraints in this solver are:\n"; | |
| 875 | ✗ | for (const std::string& name : constraintNamesFromSolverAtWaypoint(j + 1)) | |
| 876 | ✗ | err_msg << name << "\n"; | |
| 877 | hppDout(warning, err_msg.str()); | ||
| 878 | } | ||
| 879 | ✗ | assert(ok); | |
| 880 | } | ||
| 881 | } | ||
| 882 | |||
| 883 | ✗ | bool StatesPathFinder::analyseOptimizationProblem( | |
| 884 | const graph::Edges_t& transitions, core::ProblemConstPtr_t _problem) { | ||
| 885 | typedef constraints::JointConstPtr_t JointConstPtr_t; | ||
| 886 | typedef core::RelativeMotion RelativeMotion; | ||
| 887 | |||
| 888 | ✗ | OptimizationData& d = *optData_; | |
| 889 | // map from pair of joint indices to vectors of constraints | ||
| 890 | typedef std::map<std::pair<size_type, size_type>, NumericalConstraints_t> | ||
| 891 | JointConstraintMap; | ||
| 892 | ✗ | JointConstraintMap jcmap; | |
| 893 | |||
| 894 | // iterate over all the transitions, propagate only constrained pairs | ||
| 895 | ✗ | for (std::size_t i = 0; i <= transitions.size() - 1; ++i) { | |
| 896 | // get index of the transition | ||
| 897 | ✗ | std::size_t transIdx = transitions.size() - 1 - i; | |
| 898 | ✗ | const EdgePtr_t& edge = transitions[transIdx]; | |
| 899 | ✗ | RelativeMotion::matrix_type m = edge->relativeMotion(); | |
| 900 | |||
| 901 | // check through the pairs already existing in jcmap | ||
| 902 | ✗ | JointConstraintMap::iterator it = jcmap.begin(); | |
| 903 | ✗ | while (it != jcmap.end()) { | |
| 904 | RelativeMotion::RelativeMotionType rmt = | ||
| 905 | ✗ | m(it->first.first, it->first.second); | |
| 906 | ✗ | if (rmt == RelativeMotion::RelativeMotionType::Unconstrained) { | |
| 907 | ✗ | JointConstraintMap::iterator toErase = it; | |
| 908 | ✗ | ++it; | |
| 909 | ✗ | jcmap.erase(toErase); | |
| 910 | } else { | ||
| 911 | ✗ | ++it; | |
| 912 | } | ||
| 913 | } | ||
| 914 | ✗ | NumericalConstraints_t currentConstraints; | |
| 915 | ✗ | if (transIdx == transitions.size() - 1 && !goalDefinedByConstraints_) { | |
| 916 | // get the constraints from the goal state | ||
| 917 | ✗ | currentConstraints = transitions[transIdx] | |
| 918 | ✗ | ->targetConstraint() | |
| 919 | ✗ | ->configProjector() | |
| 920 | ✗ | ->solver() | |
| 921 | ✗ | .constraints(); | |
| 922 | } else { | ||
| 923 | ✗ | currentConstraints = d.solvers[transIdx].constraints(); | |
| 924 | } | ||
| 925 | // loop through all constraints in the target node of the transition | ||
| 926 | ✗ | for (auto constraint : currentConstraints) { | |
| 927 | std::pair<JointConstPtr_t, JointConstPtr_t> jointPair = | ||
| 928 | ✗ | constraint->functionPtr()->dependsOnRelPoseBetween(_problem->robot()); | |
| 929 | ✗ | JointConstPtr_t joint1 = jointPair.first; | |
| 930 | ✗ | size_type index1 = RelativeMotion::idx(joint1); | |
| 931 | ✗ | JointConstPtr_t joint2 = jointPair.second; | |
| 932 | ✗ | size_type index2 = RelativeMotion::idx(joint2); | |
| 933 | |||
| 934 | // ignore constraint if it involves the same joint | ||
| 935 | ✗ | if (index1 == index2) continue; | |
| 936 | |||
| 937 | // check that the two joints are constrained in the transition | ||
| 938 | ✗ | RelativeMotion::RelativeMotionType rmt = m(index1, index2); | |
| 939 | ✗ | if (rmt == RelativeMotion::RelativeMotionType::Unconstrained) continue; | |
| 940 | |||
| 941 | // insert if necessary | ||
| 942 | JointConstraintMap::iterator next = | ||
| 943 | jcmap | ||
| 944 | ✗ | .insert(JointConstraintMap::value_type( | |
| 945 | ✗ | std::make_pair(index1, index2), NumericalConstraints_t())) | |
| 946 | ✗ | .first; | |
| 947 | // if constraint is not in map, insert it | ||
| 948 | ✗ | if (find_if(next->second.begin(), next->second.end(), | |
| 949 | ✗ | [&constraint](const ImplicitPtr_t& arg) { | |
| 950 | ✗ | return *arg == *constraint; | |
| 951 | ✗ | }) == next->second.end()) { | |
| 952 | ✗ | next->second.push_back(constraint); | |
| 953 | } | ||
| 954 | } | ||
| 955 | } | ||
| 956 | // at this point jcmap contains all the constraints that | ||
| 957 | // - depend on relative pose between 2 joints j1 and j2, | ||
| 958 | // - are present in the solver of any waypoint wp_i | ||
| 959 | // - j1 and j2 are constrained by all the transitions from q_init to wp_i | ||
| 960 | // | ||
| 961 | // in the following we test that q_init satisfies the above constraints | ||
| 962 | // otherwise the list of transitions is discarded | ||
| 963 | ✗ | if (jcmap.size() == 0) { | |
| 964 | ✗ | return true; | |
| 965 | } | ||
| 966 | |||
| 967 | ✗ | Solver_t analyseSolver(_problem->robot()->configSpace()); | |
| 968 | ✗ | analyseSolver.errorThreshold( | |
| 969 | ✗ | _problem->getParameter("StatesPathFinder/errorThreshold").floatValue()); | |
| 970 | // iterate through all the pairs that are left, | ||
| 971 | // and check that the initial config satisfies all the constraints | ||
| 972 | ✗ | for (JointConstraintMap::iterator it(jcmap.begin()); it != jcmap.end(); | |
| 973 | ✗ | it++) { | |
| 974 | ✗ | NumericalConstraints_t constraintList = it->second; | |
| 975 | hppDout(info, "Constraints involving joints " | ||
| 976 | << it->first.first << " and " << it->first.second | ||
| 977 | << " should be satisfied at q init"); | ||
| 978 | ✗ | for (NumericalConstraints_t::iterator ctrIt(constraintList.begin()); | |
| 979 | ✗ | ctrIt != constraintList.end(); ++ctrIt) { | |
| 980 | ✗ | analyseSolver.add((*ctrIt)->copy()); | |
| 981 | } | ||
| 982 | } | ||
| 983 | // initialize the right hand side with the initial config | ||
| 984 | ✗ | analyseSolver.rightHandSideFromConfig(q1_); | |
| 985 | ✗ | if (analyseSolver.isSatisfied(q1_)) { | |
| 986 | ✗ | return true; | |
| 987 | } | ||
| 988 | hppDout(info, | ||
| 989 | "Analysis found initial configuration does not satisfy constraint"); | ||
| 990 | ✗ | return false; | |
| 991 | } | ||
| 992 | |||
| 993 | ✗ | void StatesPathFinder::initializeRHS(std::size_t j) { | |
| 994 | ✗ | OptimizationData& d = *optData_; | |
| 995 | ✗ | Solver_t& solver(d.solvers[j]); | |
| 996 | ✗ | for (std::size_t i = 0; i < constraints_.size(); ++i) { | |
| 997 | ✗ | const ImplicitPtr_t& c(constraints_[i]); | |
| 998 | ✗ | bool ok = true; | |
| 999 | ✗ | switch (d.M_status((size_type)i, (size_type)j)) { | |
| 1000 | ✗ | case OptimizationData::EQUAL_TO_PREVIOUS: | |
| 1001 | ✗ | assert(j != 0); | |
| 1002 | ✗ | ok = solver.rightHandSideFromConfig(c, d.waypoint.col(j - 1)); | |
| 1003 | ✗ | break; | |
| 1004 | ✗ | case OptimizationData::EQUAL_TO_INIT: | |
| 1005 | ✗ | ok = solver.rightHandSideFromConfig(c, d.q1); | |
| 1006 | ✗ | break; | |
| 1007 | ✗ | case OptimizationData::EQUAL_TO_GOAL: | |
| 1008 | ✗ | assert(!goalDefinedByConstraints_); | |
| 1009 | ✗ | ok = solver.rightHandSideFromConfig(c, d.q2); | |
| 1010 | ✗ | break; | |
| 1011 | ✗ | case OptimizationData::ABSENT: | |
| 1012 | default:; | ||
| 1013 | } | ||
| 1014 | ✗ | ok |= contains(solver, constraints_[i]); | |
| 1015 | ✗ | if (!ok) { | |
| 1016 | ✗ | std::ostringstream err_msg; | |
| 1017 | ✗ | err_msg << "\nConstraint " << i << " missing for waypoint " << j + 1 | |
| 1018 | ✗ | << " (" << c->function().name() << ")\n" | |
| 1019 | ✗ | << "The constraints in this solver are:\n"; | |
| 1020 | ✗ | for (const std::string& name : constraintNamesFromSolverAtWaypoint(j + 1)) | |
| 1021 | ✗ | err_msg << name << "\n"; | |
| 1022 | hppDout(warning, err_msg.str()); | ||
| 1023 | } | ||
| 1024 | ✗ | assert(ok); | |
| 1025 | } | ||
| 1026 | } | ||
| 1027 | |||
| 1028 | ✗ | void StatesPathFinder::initWPRandom(std::size_t wp) { | |
| 1029 | ✗ | assert(wp >= 1 && wp <= (std::size_t)optData_->waypoint.cols()); | |
| 1030 | ✗ | initializeRHS(wp - 1); | |
| 1031 | ✗ | optData_->waypoint.col(wp - 1) = problem()->configurationShooter()->shoot(); | |
| 1032 | } | ||
| 1033 | ✗ | void StatesPathFinder::initWPNear(std::size_t wp) { | |
| 1034 | ✗ | assert(wp >= 1 && wp <= (std::size_t)optData_->waypoint.cols()); | |
| 1035 | ✗ | initializeRHS(wp - 1); | |
| 1036 | ✗ | if (wp == 1) | |
| 1037 | ✗ | optData_->waypoint.col(wp - 1) = optData_->q1; | |
| 1038 | else | ||
| 1039 | ✗ | optData_->waypoint.col(wp - 1) = optData_->waypoint.col(wp - 2); | |
| 1040 | } | ||
| 1041 | ✗ | void StatesPathFinder::initWP(std::size_t wp, ConfigurationIn_t q) { | |
| 1042 | ✗ | assert(wp >= 1 && wp <= (std::size_t)optData_->waypoint.cols()); | |
| 1043 | ✗ | initializeRHS(wp - 1); | |
| 1044 | ✗ | optData_->waypoint.col(wp - 1) = q; | |
| 1045 | } | ||
| 1046 | |||
| 1047 | ✗ | StatesPathFinder::SolveStepStatus StatesPathFinder::solveStep(std::size_t wp) { | |
| 1048 | ✗ | assert(wp >= 1 && wp <= (std::size_t)optData_->waypoint.cols()); | |
| 1049 | ✗ | std::size_t j = wp - 1; | |
| 1050 | ✗ | Solver_t& solver(optData_->solvers[j]); | |
| 1051 | Solver_t::Status status = | ||
| 1052 | ✗ | solver.solve(optData_->waypoint.col(j), | |
| 1053 | ✗ | constraints::solver::lineSearch::Backtracking()); | |
| 1054 | ✗ | if (status == Solver_t::SUCCESS) { | |
| 1055 | ✗ | assert(checkWaypointRightHandSide(j)); | |
| 1056 | ✗ | const graph::Edges_t& edges = lastBuiltTransitions_; | |
| 1057 | ✗ | core::ValidationReportPtr_t report; | |
| 1058 | // check collision based on preceeding edge to the waypoint | ||
| 1059 | ✗ | if (!edges[j]->pathValidation()->validate(optData_->waypoint.col(j), | |
| 1060 | report)) | ||
| 1061 | ✗ | return SolveStepStatus::COLLISION_BEFORE; | |
| 1062 | // if wp is not the goal node, check collision based on following edge | ||
| 1063 | ✗ | if (j < edges.size() - 1 && !edges[j + 1]->pathValidation()->validate( | |
| 1064 | ✗ | optData_->waypoint.col(j), report)) { | |
| 1065 | ✗ | return SolveStepStatus::COLLISION_AFTER; | |
| 1066 | } | ||
| 1067 | ✗ | return SolveStepStatus::VALID_SOLUTION; | |
| 1068 | } | ||
| 1069 | ✗ | return SolveStepStatus::NO_SOLUTION; | |
| 1070 | } | ||
| 1071 | |||
| 1072 | ✗ | std::string StatesPathFinder::displayConfigsSolved() const { | |
| 1073 | ✗ | const OptimizationData& d = *optData_; | |
| 1074 | ✗ | std::ostringstream oss; | |
| 1075 | ✗ | oss << "configs = [" << std::endl; | |
| 1076 | ✗ | oss << " " << pinocchio::displayConfig(d.q1) << ", # 0" << std::endl; | |
| 1077 | ✗ | for (size_type j = 0; j < d.waypoint.cols(); j++) | |
| 1078 | ✗ | oss << " " << pinocchio::displayConfig(d.waypoint.col(j)) << ", # " | |
| 1079 | ✗ | << j + 1 << std::endl; | |
| 1080 | ✗ | if (!goalDefinedByConstraints_) { | |
| 1081 | ✗ | oss << " " << pinocchio::displayConfig(d.q2) << " # " | |
| 1082 | ✗ | << d.waypoint.cols() + 1 << std::endl; | |
| 1083 | } | ||
| 1084 | ✗ | oss << "]" << std::endl; | |
| 1085 | ✗ | std::string ans = oss.str(); | |
| 1086 | hppDout(info, ans); | ||
| 1087 | ✗ | return ans; | |
| 1088 | } | ||
| 1089 | |||
| 1090 | // Get a configuration in accordance with the statuts matrix at a step j for the | ||
| 1091 | // constraint i | ||
| 1092 | ✗ | Configuration_t StatesPathFinder::getConfigStatus(size_type i, | |
| 1093 | size_type j) const { | ||
| 1094 | ✗ | switch (optData_->M_status(i, j)) { | |
| 1095 | ✗ | case OptimizationData::EQUAL_TO_PREVIOUS: | |
| 1096 | ✗ | return optData_->waypoint.col(j - 1); | |
| 1097 | ✗ | case OptimizationData::EQUAL_TO_INIT: | |
| 1098 | ✗ | return optData_->q1; | |
| 1099 | ✗ | case OptimizationData::EQUAL_TO_GOAL: | |
| 1100 | ✗ | return optData_->q2; | |
| 1101 | ✗ | default: | |
| 1102 | ✗ | return optData_->waypoint.col(j); | |
| 1103 | } | ||
| 1104 | } | ||
| 1105 | |||
| 1106 | // Get the right hand side of a constraint w.r.t a set configuration for this | ||
| 1107 | // constraint | ||
| 1108 | ✗ | vector_t StatesPathFinder::getConstraintRHS(ImplicitPtr_t constraint, | |
| 1109 | Configuration_t q) const { | ||
| 1110 | ✗ | LiegroupElement rhs(constraint->copy()->function().outputSpace()); | |
| 1111 | ✗ | constraint->rightHandSideFromConfig(q, rhs); | |
| 1112 | ✗ | return rhs.vector(); | |
| 1113 | } | ||
| 1114 | |||
| 1115 | // Hash a vector of right hand side into a long unsigned integer | ||
| 1116 | ✗ | size_t StatesPathFinder::hashRHS(vector_t rhs) const { | |
| 1117 | ✗ | std::stringstream ss; | |
| 1118 | ✗ | ss << std::setprecision(3) << (0.01 < rhs.array().abs()).select(rhs, 0.0f); | |
| 1119 | ✗ | return std::hash<std::string>{}(ss.str()); | |
| 1120 | } | ||
| 1121 | |||
| 1122 | // Check if a solution (a list of transitions) contains impossible to solve | ||
| 1123 | // steps due to inevitable collisions. A step is impossible to solve if it has | ||
| 1124 | // two constraints set from init or goal which have produced a collision between | ||
| 1125 | // objects constrained by them. | ||
| 1126 | // The list of such known constraint pairs are memorized in pairMap table and | ||
| 1127 | // individually in constraintMap. | ||
| 1128 | // | ||
| 1129 | // Return : true if no impossible to solve steps, false otherwise | ||
| 1130 | ✗ | bool StatesPathFinder::checkSolvers( | |
| 1131 | ConstraintMap_t const& pairMap, | ||
| 1132 | ConstraintMap_t const& constraintMap) const { | ||
| 1133 | // do nothing if there is no known incompatible constraint pairs. | ||
| 1134 | ✗ | if (constraintMap.empty()) return true; | |
| 1135 | |||
| 1136 | // for each steps of the solution | ||
| 1137 | ✗ | for (long unsigned i{0}; i < optData_->solvers.size(); i++) { | |
| 1138 | ✗ | std::vector<std::pair<ImplicitPtr_t, Configuration_t>> constraints{}; | |
| 1139 | |||
| 1140 | // gather all constraints of this step which are set from init or goal | ||
| 1141 | // configuration | ||
| 1142 | ✗ | for (long unsigned j{0}; j < constraints_.size(); j++) { | |
| 1143 | ✗ | auto c = constraints_[j]; | |
| 1144 | ✗ | auto status = optData_->M_status(j, i); | |
| 1145 | ✗ | if (status != OptimizationData::EQUAL_TO_INIT && | |
| 1146 | status != OptimizationData::EQUAL_TO_GOAL) // if not init or goal | ||
| 1147 | ✗ | continue; | |
| 1148 | ✗ | auto q = getConfigStatus(j, i); | |
| 1149 | ✗ | auto name = std::hash<std::string>{}(c->function().name()); | |
| 1150 | ✗ | if (constraintMap.count(name)) | |
| 1151 | ✗ | constraints.push_back(std::make_pair(c, q)); | |
| 1152 | } | ||
| 1153 | |||
| 1154 | // if there are less than two constraints gathered, go to next step | ||
| 1155 | ✗ | if (constraints.size() < 2) continue; | |
| 1156 | |||
| 1157 | // else, check if there is a pair of constraints in the table of known | ||
| 1158 | // incompatible pairs | ||
| 1159 | ✗ | for (auto& c1 : constraints) { | |
| 1160 | ✗ | auto rhs_1 = hashRHS(getConstraintRHS(std::get<0>(c1), std::get<1>(c1))); | |
| 1161 | auto name_1 = | ||
| 1162 | ✗ | std::hash<std::string>{}(std::get<0>(c1)->function().name()); | |
| 1163 | ✗ | if (constraintMap.count(name_1)) | |
| 1164 | ✗ | for (auto& c2 : constraints) { | |
| 1165 | auto rhs_2 = | ||
| 1166 | ✗ | hashRHS(getConstraintRHS(std::get<0>(c2), std::get<1>(c2))); | |
| 1167 | auto name_2 = | ||
| 1168 | ✗ | std::hash<std::string>{}(std::get<0>(c2)->function().name()); | |
| 1169 | ✗ | auto namesPair = name_1 * name_2; | |
| 1170 | ✗ | auto rhsPair = rhs_1 * rhs_2; | |
| 1171 | ✗ | if (name_1 != name_2 && pairMap.count(namesPair) && | |
| 1172 | ✗ | pairMap.at(namesPair) == rhsPair) | |
| 1173 | ✗ | return false; | |
| 1174 | } | ||
| 1175 | } | ||
| 1176 | } | ||
| 1177 | |||
| 1178 | ✗ | return true; | |
| 1179 | } | ||
| 1180 | |||
| 1181 | ✗ | core::JointConstPtr_t StatesPathFinder::maximalJoint(size_t const wp, | |
| 1182 | core::JointConstPtr_t a) { | ||
| 1183 | ✗ | const auto& current_edge = lastBuiltTransitions_[wp + 1]; | |
| 1184 | ✗ | core::RelativeMotion::matrix_type m = current_edge->relativeMotion(); | |
| 1185 | |||
| 1186 | ✗ | size_t ida = core::RelativeMotion::idx(a); | |
| 1187 | |||
| 1188 | ✗ | core::JointConstPtr_t last = nullptr; | |
| 1189 | ✗ | core::JointConstPtr_t current = a; | |
| 1190 | |||
| 1191 | ✗ | while (current != nullptr) { | |
| 1192 | ✗ | auto parent = current->parentJoint(); | |
| 1193 | ✗ | size_t idp = core::RelativeMotion::idx(parent); | |
| 1194 | ✗ | last = current; | |
| 1195 | ✗ | if (parent && m(ida, idp)) | |
| 1196 | ✗ | current = current->parentJoint(); | |
| 1197 | else | ||
| 1198 | ✗ | break; | |
| 1199 | } | ||
| 1200 | |||
| 1201 | ✗ | return last; | |
| 1202 | } | ||
| 1203 | |||
| 1204 | // For a certain step wp during solving check for collision impossible to solve. | ||
| 1205 | // If there is any store the constraints involved and stop the resolution | ||
| 1206 | // | ||
| 1207 | // Return : true if there is no collision or impossible to solve ones, false | ||
| 1208 | // otherwise. | ||
| 1209 | ✗ | bool StatesPathFinder::saveIncompatibleRHS(ConstraintMap_t& pairMap, | |
| 1210 | ConstraintMap_t& constraintMap, | ||
| 1211 | size_type const wp) { | ||
| 1212 | ✗ | core::ValidationReportPtr_t validationReport; | |
| 1213 | ✗ | auto q = optData_->waypoint.col(wp - 1); | |
| 1214 | ✗ | bool nocollision{true}; | |
| 1215 | |||
| 1216 | core::CollisionValidationPtr_t collisionValidations = | ||
| 1217 | ✗ | core::CollisionValidation::create(problem_->robot()); | |
| 1218 | ✗ | collisionValidations->checkParameterized(true); | |
| 1219 | ✗ | collisionValidations->computeAllContacts(true); | |
| 1220 | |||
| 1221 | // If there was a collision in the last configuration | ||
| 1222 | ✗ | if (!collisionValidations->validate(q, validationReport)) { | |
| 1223 | ✗ | auto allReports = HPP_DYNAMIC_PTR_CAST(core::AllCollisionsValidationReport, | |
| 1224 | validationReport); | ||
| 1225 | |||
| 1226 | // check all collision reports between joints | ||
| 1227 | ✗ | for (auto& report : allReports->collisionReports) { | |
| 1228 | // Store the two joints involved | ||
| 1229 | ✗ | core::JointConstPtr_t j1 = report->object1->joint(); | |
| 1230 | ✗ | core::JointConstPtr_t j2 = report->object2->joint(); | |
| 1231 | |||
| 1232 | // check that there is indeed two joints | ||
| 1233 | ✗ | if (!j1 || !j2) return nocollision; | |
| 1234 | |||
| 1235 | // get the maximal parent joint which are constrained with their child | ||
| 1236 | ✗ | j1 = maximalJoint(wp, j1); | |
| 1237 | ✗ | j2 = maximalJoint(wp, j2); | |
| 1238 | |||
| 1239 | // Function to check if two joints are equals, bye their address is | ||
| 1240 | // nullptr, by their value otherwise | ||
| 1241 | ✗ | auto equalJoints = [](core::JointConstPtr_t a, core::JointConstPtr_t b) { | |
| 1242 | ✗ | return (a && b) ? *a == *b : a == b; | |
| 1243 | }; | ||
| 1244 | |||
| 1245 | // std::cout << "test are constrained for j1 & j2: " << areConstrained(wp, | ||
| 1246 | // j1, j2) << std::endl; | ||
| 1247 | |||
| 1248 | typedef std::pair<core::JointConstPtr_t, size_t> jointOfConstraint; | ||
| 1249 | |||
| 1250 | // Get all constraints which involve a joint | ||
| 1251 | ✗ | auto associatedConstraints = [&](core::JointConstPtr_t j) { | |
| 1252 | ✗ | std::vector<jointOfConstraint> constraints{}; | |
| 1253 | ✗ | for (size_t i{0}; i < constraints_.size(); i++) { | |
| 1254 | ✗ | auto constraint = constraints_[i]; | |
| 1255 | auto joints = | ||
| 1256 | ✗ | constraint->doesConstrainRelPoseBetween(problem_->robot()); | |
| 1257 | ✗ | if (equalJoints(j, std::get<0>(joints)) || | |
| 1258 | ✗ | equalJoints(j, std::get<1>(joints))) { | |
| 1259 | ✗ | auto joint = (j == std::get<0>(joints)) ? std::get<1>(joints) | |
| 1260 | ✗ | : std::get<0>(joints); | |
| 1261 | ✗ | constraints.push_back(std::make_pair(joint, i)); | |
| 1262 | } | ||
| 1263 | } | ||
| 1264 | ✗ | return constraints; | |
| 1265 | ✗ | }; | |
| 1266 | |||
| 1267 | // We get all the constraints which contain j1 | ||
| 1268 | ✗ | auto constraints_j1 = associatedConstraints(j1); | |
| 1269 | |||
| 1270 | ✗ | const auto& current_edge = lastBuiltTransitions_[wp + 1]; | |
| 1271 | ✗ | core::RelativeMotion::matrix_type m = current_edge->relativeMotion(); | |
| 1272 | |||
| 1273 | ✗ | std::vector<short> visited(constraints_.size(), 0); | |
| 1274 | std::function<std::vector<int>(core::JointConstPtr_t, jointOfConstraint, | ||
| 1275 | int)> | ||
| 1276 | ✗ | exploreJOC; | |
| 1277 | |||
| 1278 | // Check if a joint is indirectly co-constrained with an other, return the | ||
| 1279 | // indices of their respective constraints | ||
| 1280 | ✗ | exploreJOC = [&](core::JointConstPtr_t j, jointOfConstraint current, | |
| 1281 | int initial) { | ||
| 1282 | ✗ | size_t constraint_index = std::get<1>(current); | |
| 1283 | ✗ | visited[constraint_index]++; | |
| 1284 | ✗ | core::JointConstPtr_t current_joint = std::get<0>(current); | |
| 1285 | ✗ | auto iconstraint = constraints_[constraint_index]; | |
| 1286 | ✗ | auto JOCs = associatedConstraints(current_joint); | |
| 1287 | ✗ | auto id_cj = core::RelativeMotion::idx(current_joint); | |
| 1288 | |||
| 1289 | ✗ | for (auto& joc : JOCs) { | |
| 1290 | ✗ | size_t ci = std::get<1>(joc); | |
| 1291 | ✗ | core::JointConstPtr_t ji = std::get<0>(joc); | |
| 1292 | ✗ | auto id_ji = core::RelativeMotion::idx(ji); | |
| 1293 | ✗ | if (m(id_cj, id_ji) == | |
| 1294 | core::RelativeMotion::RelativeMotionType::Unconstrained) | ||
| 1295 | ✗ | continue; | |
| 1296 | ✗ | if (equalJoints(ji, j)) | |
| 1297 | ✗ | return std::vector<int>{initial, (int)ci}; | |
| 1298 | ✗ | else if (visited[ci] < 2) { | |
| 1299 | ✗ | return exploreJOC(j, joc, initial); | |
| 1300 | } | ||
| 1301 | } | ||
| 1302 | ✗ | return std::vector<int>{-1, -1}; | |
| 1303 | ✗ | }; | |
| 1304 | |||
| 1305 | // get the indices of the constraints associated to the two joints | ||
| 1306 | ✗ | auto getIndices = [&]() -> std::vector<int> { | |
| 1307 | ✗ | for (auto& joc : constraints_j1) { | |
| 1308 | ✗ | visited[std::get<1>(joc)] = 1; | |
| 1309 | ✗ | auto indices = exploreJOC(j2, joc, (int)std::get<1>(joc)); | |
| 1310 | ✗ | if (indices[0] >= 0 || indices[1] >= 0) return indices; | |
| 1311 | } | ||
| 1312 | ✗ | return std::vector<int>{-1, -1}; | |
| 1313 | ✗ | }; | |
| 1314 | |||
| 1315 | // indices contains the two indices of the constraints that constraint | ||
| 1316 | // pose of j1 with respect to j2, if any, or { -1, -1} | ||
| 1317 | ✗ | auto indices = getIndices(); | |
| 1318 | |||
| 1319 | // Make sure indices are all defined | ||
| 1320 | ✗ | if (indices[0] < 0 || indices[1] < 0) return nocollision; | |
| 1321 | |||
| 1322 | // for each of the two constraint identified | ||
| 1323 | ✗ | std::vector<std::pair<size_t, size_t>> constraints{}; | |
| 1324 | ✗ | for (auto ic : indices) { | |
| 1325 | // check that there are set from goal or init configurations | ||
| 1326 | ✗ | auto status = optData_->M_status((size_t)ic, wp - 1); | |
| 1327 | ✗ | if (status != OptimizationData::EQUAL_TO_INIT && | |
| 1328 | status != OptimizationData::EQUAL_TO_GOAL) | ||
| 1329 | ✗ | return nocollision; | |
| 1330 | |||
| 1331 | // if so prepare to store them in the tables of known incompatible | ||
| 1332 | // constraints | ||
| 1333 | ✗ | auto c = constraints_[(size_t)ic]; | |
| 1334 | ✗ | auto rhs = hashRHS(getConstraintRHS(c, q)); | |
| 1335 | ✗ | auto name = std::hash<std::string>{}(c->function().name()); | |
| 1336 | |||
| 1337 | ✗ | constraints.push_back(std::make_pair(name, rhs)); | |
| 1338 | } | ||
| 1339 | |||
| 1340 | // then add them both in the tables of incompatible constraints | ||
| 1341 | ✗ | nocollision = false; | |
| 1342 | |||
| 1343 | // first, individually, in constraintMap | ||
| 1344 | ✗ | for (auto& c : constraints) | |
| 1345 | ✗ | if (!constraintMap.count(std::get<0>(c))) | |
| 1346 | ✗ | constraintMap[std::get<0>(c)] = std::get<1>(c); | |
| 1347 | |||
| 1348 | // then, both merged together in pairMap | ||
| 1349 | auto names = | ||
| 1350 | ✗ | std::get<0>(constraints[0]) * std::get<0>(constraints[1]); // key | |
| 1351 | auto rhs = | ||
| 1352 | ✗ | std::get<1>(constraints[0]) * std::get<1>(constraints[1]); // value | |
| 1353 | |||
| 1354 | ✗ | if (!pairMap.count(names)) pairMap[names] = rhs; | |
| 1355 | } | ||
| 1356 | } | ||
| 1357 | |||
| 1358 | ✗ | return nocollision; | |
| 1359 | } | ||
| 1360 | |||
| 1361 | ✗ | bool StatesPathFinder::solveOptimizationProblem() { | |
| 1362 | ✗ | static ConstraintMap_t pairMap{}; | |
| 1363 | ✗ | static ConstraintMap_t constraintMap{}; | |
| 1364 | |||
| 1365 | // check if the solution is feasible (no inevitable collision), if not abort | ||
| 1366 | // the solving | ||
| 1367 | ✗ | if (!checkSolvers(pairMap, constraintMap)) { | |
| 1368 | hppDout(info, "Path is invalid for collision is inevitable"); | ||
| 1369 | ✗ | return false; | |
| 1370 | } | ||
| 1371 | |||
| 1372 | ✗ | OptimizationData& d = *optData_; | |
| 1373 | // Try to solve with sets of random configs for each waypoint | ||
| 1374 | std::size_t nTriesMax = | ||
| 1375 | ✗ | problem_->getParameter("StatesPathFinder/nTriesUntilBacktrack") | |
| 1376 | ✗ | .intValue(); | |
| 1377 | ✗ | std::size_t nTriesMax1 = nTriesMax * 10; // more tries for the first waypoint | |
| 1378 | ✗ | std::size_t nFailsMax = | |
| 1379 | nTriesMax * 20; // fails before reseting the whole solution | ||
| 1380 | ✗ | std::size_t nBadSolvesMax = | |
| 1381 | nTriesMax * 50; // bad solve fails before reseting the whole solution | ||
| 1382 | ✗ | std::vector<std::size_t> nTriesDone(d.solvers.size() + 1, 0); | |
| 1383 | ✗ | std::size_t nFails = 0; | |
| 1384 | ✗ | std::size_t nBadSolves = 0; | |
| 1385 | ✗ | std::size_t wp = 1; // waypoint index starting at 1 (wp 0 = q1) | |
| 1386 | ✗ | std::size_t wp_max = 0; // all waypoints up to this index are valid solved | |
| 1387 | ✗ | matrix_t longestSolved(d.nq, d.N); | |
| 1388 | ✗ | longestSolved.setZero(); | |
| 1389 | ✗ | while (wp <= d.solvers.size()) { | |
| 1390 | ✗ | if (wp == 1) { | |
| 1391 | // stop if number of tries for the first waypoint exceeds | ||
| 1392 | ✗ | if (nTriesDone[1] >= nTriesMax1) { | |
| 1393 | // if cannot solve all the way, return longest VALID sequence | ||
| 1394 | ✗ | d.waypoint = longestSolved; | |
| 1395 | ✗ | return false; | |
| 1396 | } | ||
| 1397 | // Reset the fail counter while the solution is empty | ||
| 1398 | ✗ | nFails = 0; | |
| 1399 | ✗ | nBadSolves = 0; | |
| 1400 | |||
| 1401 | ✗ | } else if (nFails >= nFailsMax || nBadSolves >= nBadSolvesMax) { | |
| 1402 | // Completely reset a solution when too many tries have failed | ||
| 1403 | |||
| 1404 | // update the longest valid sequence of waypoints solved | ||
| 1405 | ✗ | if (wp - 1 > wp_max) { | |
| 1406 | // update the maximum index of valid waypoint | ||
| 1407 | ✗ | wp_max = wp - 1; | |
| 1408 | // save the sequence | ||
| 1409 | ✗ | longestSolved.leftCols(wp_max) = d.waypoint.leftCols(wp_max); | |
| 1410 | } | ||
| 1411 | |||
| 1412 | ✗ | std::fill(nTriesDone.begin() + 2, nTriesDone.end(), 0); | |
| 1413 | ✗ | wp = 1; | |
| 1414 | |||
| 1415 | #ifdef HPP_DEBUG | ||
| 1416 | if (nFails >= nFailsMax) { | ||
| 1417 | hppDout(warning, " Solution " | ||
| 1418 | << graphData_->idxSol | ||
| 1419 | << ": too many collisions. Resetting back to WP1"); | ||
| 1420 | } | ||
| 1421 | if (nBadSolves >= nBadSolvesMax) { | ||
| 1422 | hppDout(warning, | ||
| 1423 | " Solution " | ||
| 1424 | << graphData_->idxSol | ||
| 1425 | << ": too many bad solve statuses. Resetting back to WP1"); | ||
| 1426 | } | ||
| 1427 | #endif | ||
| 1428 | |||
| 1429 | ✗ | continue; | |
| 1430 | |||
| 1431 | ✗ | } else if (nTriesDone[wp] >= nTriesMax) { | |
| 1432 | // enough tries for a waypoint: backtrack | ||
| 1433 | |||
| 1434 | // update the longest valid sequence of waypoints solved | ||
| 1435 | ✗ | if (wp - 1 > wp_max) { | |
| 1436 | // update the maximum index of valid waypoint | ||
| 1437 | ✗ | wp_max = wp - 1; | |
| 1438 | // save the sequence | ||
| 1439 | ✗ | longestSolved.leftCols(wp_max) = d.waypoint.leftCols(wp_max); | |
| 1440 | } | ||
| 1441 | |||
| 1442 | do { | ||
| 1443 | ✗ | nTriesDone[wp] = 0; | |
| 1444 | ✗ | wp--; // backtrack: try a new solution for the latest waypoint | |
| 1445 | ✗ | } while (wp > 1 && | |
| 1446 | ✗ | (d.isTargetWaypoint[wp - 1] || nTriesDone[wp] >= nTriesMax)); | |
| 1447 | |||
| 1448 | ✗ | continue; | |
| 1449 | } | ||
| 1450 | |||
| 1451 | // Initialize right hand sides, and | ||
| 1452 | // Choose a starting configuration for the solver.solve method: | ||
| 1453 | // - from previous waypoint if it's the first time we see this solver | ||
| 1454 | // given current solvers 0 to j-1 | ||
| 1455 | // - with a random configuration if the other initialization has been | ||
| 1456 | // tried and failed | ||
| 1457 | ✗ | if (nTriesDone[wp] == 0) | |
| 1458 | ✗ | initWPNear(wp); | |
| 1459 | else | ||
| 1460 | ✗ | initWPRandom(wp); | |
| 1461 | |||
| 1462 | ✗ | nTriesDone[wp]++; // Backtrack to last state when this gets too big | |
| 1463 | |||
| 1464 | ✗ | SolveStepStatus out = solveStep(wp); | |
| 1465 | hppDout(info, "solveStep exit code at WP" << wp << ": " << out); | ||
| 1466 | ✗ | switch (out) { | |
| 1467 | ✗ | case SolveStepStatus::VALID_SOLUTION: // Valid solution, go to next | |
| 1468 | // waypoint | ||
| 1469 | ✗ | wp++; | |
| 1470 | ✗ | break; | |
| 1471 | ✗ | case SolveStepStatus::NO_SOLUTION: // Bad solve status, considered usual | |
| 1472 | // so has higher threshold before | ||
| 1473 | // going back to first waypoint | ||
| 1474 | ✗ | nBadSolves++; | |
| 1475 | ✗ | break; | |
| 1476 | ✗ | case SolveStepStatus::COLLISION_BEFORE: // Collision. If that happens too | |
| 1477 | // much, go back to first | ||
| 1478 | // waypoint | ||
| 1479 | case SolveStepStatus::COLLISION_AFTER: | ||
| 1480 | // if collision check that it is not due to non-solvable constraints, | ||
| 1481 | // if so, store the constraints involved and abort the solving | ||
| 1482 | ✗ | if (!saveIncompatibleRHS(pairMap, constraintMap, wp)) { | |
| 1483 | hppDout(info, "Path is invalid, found inevitable collision"); | ||
| 1484 | ✗ | return false; | |
| 1485 | } | ||
| 1486 | ✗ | nFails++; | |
| 1487 | ✗ | break; | |
| 1488 | ✗ | default: | |
| 1489 | ✗ | throw(std::logic_error("Unintended exit code for solveStep")); | |
| 1490 | } | ||
| 1491 | } | ||
| 1492 | |||
| 1493 | ✗ | return true; | |
| 1494 | } | ||
| 1495 | |||
| 1496 | // Get list of configurations from solution of optimization problem | ||
| 1497 | ✗ | core::Configurations_t StatesPathFinder::getConfigList() const { | |
| 1498 | ✗ | OptimizationData& d = *optData_; | |
| 1499 | ✗ | core::Configurations_t pv; | |
| 1500 | ✗ | pv.push_back(d.q1); | |
| 1501 | ✗ | for (std::size_t i = 0; i < d.N; ++i) { | |
| 1502 | ✗ | pv.push_back(d.waypoint.col(i)); | |
| 1503 | } | ||
| 1504 | ✗ | if (!goalDefinedByConstraints_) { | |
| 1505 | ✗ | pv.push_back(d.q2); | |
| 1506 | } | ||
| 1507 | ✗ | return pv; | |
| 1508 | } | ||
| 1509 | |||
| 1510 | // Loop over all the possible paths in the constraint graph between | ||
| 1511 | // the state of the initial configuration | ||
| 1512 | // and either [the state of the final configurations if given] OR | ||
| 1513 | // [one of potential goal states if goal defined as set of constraints] | ||
| 1514 | // and compute waypoint configurations in each state. | ||
| 1515 | ✗ | core::Configurations_t StatesPathFinder::computeConfigList( | |
| 1516 | ConfigurationIn_t q1, ConfigurationIn_t q2) { | ||
| 1517 | ✗ | const graph::GraphPtr_t& graph(problem_->constraintGraph()); | |
| 1518 | ✗ | GraphSearchData& d = *graphData_; | |
| 1519 | ✗ | size_t& idxSol = d.idxSol; | |
| 1520 | |||
| 1521 | bool maxDepthReached; | ||
| 1522 | ✗ | while (!(maxDepthReached = findTransitions(d))) { // mut | |
| 1523 | // if there is a working sequence, try it first before getting another | ||
| 1524 | // transition list | ||
| 1525 | ✗ | Edges_t transitions = (nTryConfigList_ > 0) | |
| 1526 | ✗ | ? lastBuiltTransitions_ | |
| 1527 | ✗ | : getTransitionList(d, idxSol); // const, const | |
| 1528 | ✗ | while (!transitions.empty()) { | |
| 1529 | #ifdef HPP_DEBUG | ||
| 1530 | std::ostringstream ss; | ||
| 1531 | ss << " Trying solution " << idxSol << ": \n\t"; | ||
| 1532 | for (std::size_t j = 0; j < transitions.size(); ++j) | ||
| 1533 | ss << transitions[j]->name() << ", \n\t"; | ||
| 1534 | hppDout(info, ss.str()); | ||
| 1535 | #endif // HPP_DEBUG | ||
| 1536 | ✗ | if (optData_) { | |
| 1537 | ✗ | delete optData_; | |
| 1538 | ✗ | optData_ = nullptr; | |
| 1539 | } | ||
| 1540 | ✗ | optData_ = new OptimizationData(problem(), q1, q2, transitions, | |
| 1541 | ✗ | goalDefinedByConstraints_); | |
| 1542 | |||
| 1543 | ✗ | if (buildOptimizationProblem(transitions)) { | |
| 1544 | ✗ | lastBuiltTransitions_ = transitions; | |
| 1545 | ✗ | if (nTryConfigList_ > 0 || | |
| 1546 | ✗ | analyseOptimizationProblem(transitions, problem())) { | |
| 1547 | ✗ | if (solveOptimizationProblem()) { | |
| 1548 | ✗ | core::Configurations_t path = getConfigList(); | |
| 1549 | hppDout(warning, | ||
| 1550 | " Solution " << idxSol << ": solved configurations list"); | ||
| 1551 | ✗ | return path; | |
| 1552 | ✗ | } else { | |
| 1553 | hppDout(info, " Failed solution " << idxSol | ||
| 1554 | << " at step 5 (solve opt pb)"); | ||
| 1555 | } | ||
| 1556 | } else { | ||
| 1557 | hppDout(info, " Failed solution " << idxSol | ||
| 1558 | << " at step 4 (analyse opt pb)"); | ||
| 1559 | } | ||
| 1560 | } else { | ||
| 1561 | hppDout(info, | ||
| 1562 | " Failed solution " << idxSol << " at step 3 (build opt pb)"); | ||
| 1563 | } | ||
| 1564 | ✗ | transitions = getTransitionList(d, ++idxSol); | |
| 1565 | // reset of the number of tries for a sequence | ||
| 1566 | // nTryConfigList_ = 0; | ||
| 1567 | } | ||
| 1568 | } | ||
| 1569 | ✗ | core::Configurations_t empty_path; | |
| 1570 | ✗ | empty_path.push_back(q1); | |
| 1571 | ✗ | return empty_path; | |
| 1572 | } | ||
| 1573 | |||
| 1574 | ✗ | void StatesPathFinder::reset() { | |
| 1575 | // when debugging, if we want to start from a certain transition list, | ||
| 1576 | // we can set it here | ||
| 1577 | ✗ | graphData_->idxSol = 0; | |
| 1578 | ✗ | if (optData_) { | |
| 1579 | ✗ | delete optData_; | |
| 1580 | ✗ | optData_ = nullptr; | |
| 1581 | } | ||
| 1582 | ✗ | lastBuiltTransitions_.clear(); | |
| 1583 | ✗ | idxConfigList_ = 0; | |
| 1584 | ✗ | nTryConfigList_ = 0; | |
| 1585 | } | ||
| 1586 | |||
| 1587 | ✗ | void StatesPathFinder::startSolve() { | |
| 1588 | ✗ | PathPlanner::startSolve(); | |
| 1589 | ✗ | assert(problem_); | |
| 1590 | ✗ | q1_ = problem_->initConfig(); | |
| 1591 | ✗ | assert(q1_.size() > 0); | |
| 1592 | |||
| 1593 | // core::PathProjectorPtr_t pathProjector | ||
| 1594 | // (core::pathProjector::Progressive::create(inStateProblem_, 0.01)); | ||
| 1595 | // inStateProblem_->pathProjector(pathProjector); | ||
| 1596 | ✗ | inStateProblem_->pathProjector(problem_->pathProjector()); | |
| 1597 | ✗ | const graph::GraphPtr_t& graph(problem_->constraintGraph()); | |
| 1598 | ✗ | graphData_.reset(new GraphSearchData()); | |
| 1599 | ✗ | GraphSearchData& d = *graphData_; | |
| 1600 | ✗ | d.s1 = graph->getState(q1_); | |
| 1601 | ✗ | d.maxDepth = problem_->getParameter("StatesPathFinder/maxDepth").intValue(); | |
| 1602 | |||
| 1603 | ✗ | d.queue1.push_back(d.addInitState()); | |
| 1604 | ✗ | d.queueIt = d.queue1.size(); | |
| 1605 | |||
| 1606 | #ifdef HPP_DEBUG | ||
| 1607 | // Print out the names of all the states in graph in debug mode | ||
| 1608 | States_t allStates = graph->stateSelector()->getStates(); | ||
| 1609 | hppDout(info, "Constraint graph has " << allStates.size() << " nodes"); | ||
| 1610 | for (auto state : allStates) { | ||
| 1611 | hppDout(info, "State: id = " << state->id() << " name = \"" << state->name() | ||
| 1612 | << "\""); | ||
| 1613 | } | ||
| 1614 | hppDout(info, | ||
| 1615 | "Constraint graph has " << graph->nbComponents() << " components"); | ||
| 1616 | #endif | ||
| 1617 | // Detect whether the goal is defined by a configuration or by a | ||
| 1618 | // set of constraints | ||
| 1619 | ✗ | ProblemTargetPtr_t target(problem()->target()); | |
| 1620 | GoalConfigurationsPtr_t goalConfigs( | ||
| 1621 | ✗ | HPP_DYNAMIC_PTR_CAST(GoalConfigurations, target)); | |
| 1622 | ✗ | if (goalConfigs) { | |
| 1623 | ✗ | goalDefinedByConstraints_ = false; | |
| 1624 | ✗ | core::Configurations_t q2s = goalConfigs->configurations(); | |
| 1625 | ✗ | if (q2s.size() != 1) { | |
| 1626 | ✗ | std::ostringstream os; | |
| 1627 | os << "StatesPathFinder accept one and only one goal " | ||
| 1628 | ✗ | "configuration, "; | |
| 1629 | ✗ | os << q2s.size() << " provided."; | |
| 1630 | ✗ | throw std::logic_error(os.str().c_str()); | |
| 1631 | } | ||
| 1632 | ✗ | q2_ = q2s[0]; | |
| 1633 | ✗ | d.s2.push_back(graph->getState(q2_)); | |
| 1634 | ✗ | } else { | |
| 1635 | ✗ | TaskTargetPtr_t taskTarget(HPP_DYNAMIC_PTR_CAST(TaskTarget, target)); | |
| 1636 | ✗ | if (!taskTarget) { | |
| 1637 | ✗ | std::ostringstream os; | |
| 1638 | os << "StatesPathFinder only accept goal defined as " | ||
| 1639 | ✗ | "either a configuration or a set of constraints."; | |
| 1640 | ✗ | throw std::logic_error(os.str().c_str()); | |
| 1641 | } | ||
| 1642 | ✗ | assert(q2_.size() == 0); | |
| 1643 | ✗ | goalDefinedByConstraints_ = true; | |
| 1644 | ✗ | goalConstraints_ = taskTarget->constraints(); | |
| 1645 | hppDout(info, "goal defined as a set of constraints"); | ||
| 1646 | |||
| 1647 | ✗ | int maxNumConstr = -1; | |
| 1648 | ✗ | for (StatePtr_t state : graph->stateSelector()->getStates()) { | |
| 1649 | ✗ | NumericalConstraints_t stateConstr = state->numericalConstraints(); | |
| 1650 | ✗ | int numConstr = 0; | |
| 1651 | ✗ | for (auto goalConstraint : goalConstraints_) { | |
| 1652 | ✗ | if (std::find(stateConstr.begin(), stateConstr.end(), goalConstraint) != | |
| 1653 | ✗ | stateConstr.end()) { | |
| 1654 | ✗ | ++numConstr; | |
| 1655 | hppDout(info, "State \"" << state->name() << "\" " | ||
| 1656 | << "has goal constraint: \"" | ||
| 1657 | << goalConstraint->function().name() | ||
| 1658 | << "\""); | ||
| 1659 | } | ||
| 1660 | } | ||
| 1661 | ✗ | if (numConstr > maxNumConstr) { | |
| 1662 | ✗ | d.s2.clear(); | |
| 1663 | ✗ | d.s2.push_back(state); | |
| 1664 | ✗ | maxNumConstr = numConstr; | |
| 1665 | ✗ | } else if (numConstr == maxNumConstr) { | |
| 1666 | ✗ | d.s2.push_back(state); | |
| 1667 | } | ||
| 1668 | } | ||
| 1669 | ✗ | d.idxSol = 0; | |
| 1670 | } | ||
| 1671 | ✗ | reset(); | |
| 1672 | } | ||
| 1673 | |||
| 1674 | ✗ | void StatesPathFinder::oneStep() { | |
| 1675 | ✗ | if (idxConfigList_ == 0) { | |
| 1676 | // TODO: accommodate when goal is a set of constraints | ||
| 1677 | ✗ | assert(q1_.size() > 0); | |
| 1678 | ✗ | configList_ = computeConfigList(q1_, q2_); | |
| 1679 | ✗ | if (configList_.size() <= 1) { // max depth reached | |
| 1680 | ✗ | reset(); | |
| 1681 | ✗ | throw core::path_planning_failed("Maximal depth reached."); | |
| 1682 | } | ||
| 1683 | } | ||
| 1684 | ✗ | size_t& idxSol = graphData_->idxSol; | |
| 1685 | ✗ | Configuration_t q1, q2; | |
| 1686 | ✗ | if (idxConfigList_ >= configList_.size() - 1) { | |
| 1687 | ✗ | reset(); | |
| 1688 | ✗ | throw core::path_planning_failed( | |
| 1689 | ✗ | "Final config reached but goal is not reached."); | |
| 1690 | } | ||
| 1691 | ✗ | q1 = configList_[idxConfigList_]; | |
| 1692 | ✗ | q2 = configList_[idxConfigList_ + 1]; | |
| 1693 | ✗ | const graph::EdgePtr_t& edge(lastBuiltTransitions_[idxConfigList_]); | |
| 1694 | // Copy edge constraints | ||
| 1695 | ✗ | core::ConstraintSetPtr_t constraints(HPP_DYNAMIC_PTR_CAST( | |
| 1696 | ✗ | core::ConstraintSet, edge->pathConstraint()->copy())); | |
| 1697 | // Initialize right hand side | ||
| 1698 | ✗ | constraints->configProjector()->rightHandSideFromConfig(q1); | |
| 1699 | ✗ | assert(constraints->isSatisfied(q2)); | |
| 1700 | ✗ | inStateProblem_->constraints(constraints); | |
| 1701 | ✗ | inStateProblem_->pathValidation(edge->pathValidation()); | |
| 1702 | ✗ | inStateProblem_->steeringMethod(edge->steeringMethod()); | |
| 1703 | ✗ | inStateProblem_->initConfig(q1); | |
| 1704 | ✗ | inStateProblem_->resetGoalConfigs(); | |
| 1705 | ✗ | inStateProblem_->addGoalConfig(q2); | |
| 1706 | |||
| 1707 | /// use inner state planner to plan path between two configurations. | ||
| 1708 | /// these configs lie on same leaf (same RHS wrt edge constraints) | ||
| 1709 | /// eg consecutive configs in the solved config list | ||
| 1710 | core::PathPlannerPtr_t inStatePlanner( | ||
| 1711 | ✗ | core::DiffusingPlanner::create(inStateProblem_)); | |
| 1712 | ✗ | inStatePlanner->maxIterations( | |
| 1713 | ✗ | problem_->getParameter("StatesPathFinder/innerPlannerMaxIterations") | |
| 1714 | ✗ | .intValue()); | |
| 1715 | value_type innerPlannerTimeout = | ||
| 1716 | ✗ | problem_->getParameter("StatesPathFinder/innerPlannerTimeOut") | |
| 1717 | ✗ | .floatValue(); | |
| 1718 | // only set timeout if it is more than 0. default is infinity | ||
| 1719 | ✗ | if (innerPlannerTimeout > 0.) { | |
| 1720 | ✗ | inStatePlanner->timeOut(innerPlannerTimeout); | |
| 1721 | } | ||
| 1722 | hppDout(info, | ||
| 1723 | "calling InStatePlanner_.solve for transition " << idxConfigList_); | ||
| 1724 | ✗ | core::PathVectorPtr_t path; | |
| 1725 | try { | ||
| 1726 | ✗ | path = inStatePlanner->solve(); | |
| 1727 | ✗ | for (std::size_t r = 0; r < path->numberPaths() - 1; r++) | |
| 1728 | ✗ | assert(path->pathAtRank(r)->end() == path->pathAtRank(r + 1)->initial()); | |
| 1729 | ✗ | idxConfigList_++; | |
| 1730 | ✗ | if (idxConfigList_ == configList_.size() - 1) { | |
| 1731 | hppDout( | ||
| 1732 | warning, "Solution " | ||
| 1733 | << idxSol << ": Success" | ||
| 1734 | << "\n-----------------------------------------------"); | ||
| 1735 | } | ||
| 1736 | ✗ | } catch (const core::path_planning_failed& error) { | |
| 1737 | ✗ | std::ostringstream oss; | |
| 1738 | ✗ | oss << "Error " << error.what() << "\n"; | |
| 1739 | ✗ | oss << "Solution " << idxSol << ": Failed to build path at edge " | |
| 1740 | ✗ | << idxConfigList_ << ": "; | |
| 1741 | ✗ | oss << lastBuiltTransitions_[idxConfigList_]->name(); | |
| 1742 | hppDout(warning, oss.str()); | ||
| 1743 | |||
| 1744 | ✗ | idxConfigList_ = 0; | |
| 1745 | // Retry nTryMax times to build another solution for the same states list | ||
| 1746 | size_type nTryMax = | ||
| 1747 | ✗ | problem_->getParameter("StatesPathFinder/maxTriesBuildPath").intValue(); | |
| 1748 | ✗ | if (++nTryConfigList_ >= nTryMax) { | |
| 1749 | ✗ | nTryConfigList_ = 0; | |
| 1750 | ✗ | idxSol++; | |
| 1751 | } | ||
| 1752 | } | ||
| 1753 | ✗ | roadmap()->merge(inStatePlanner->roadmap()); | |
| 1754 | // if (path) { | ||
| 1755 | // core::PathOptimizerPtr_t inStateOptimizer | ||
| 1756 | // (core::pathOptimization::RandomShortcut::create(inStateProblem_)); | ||
| 1757 | // core::PathVectorPtr_t opt = inStateOptimizer->optimize(path); | ||
| 1758 | // roadmap()->insertPathVector(opt, true); | ||
| 1759 | // } | ||
| 1760 | } | ||
| 1761 | |||
| 1762 | ✗ | void StatesPathFinder::tryConnectInitAndGoals() { | |
| 1763 | ✗ | GraphSearchData& d = *graphData_; | |
| 1764 | // if start state is not one of the potential goal states, return | ||
| 1765 | ✗ | if (std::find(d.s2.begin(), d.s2.end(), d.s1) == d.s2.end()) { | |
| 1766 | ✗ | return; | |
| 1767 | } | ||
| 1768 | |||
| 1769 | // get the loop edge connecting the initial state to itself | ||
| 1770 | const graph::Edges_t& loopEdges( | ||
| 1771 | ✗ | problem_->constraintGraph()->getEdges(d.s1, d.s1)); | |
| 1772 | // check that there is 1 loop edge | ||
| 1773 | ✗ | assert(loopEdges.size() == 1); | |
| 1774 | // add the loop transition as transition list | ||
| 1775 | ✗ | GraphSearchData::state_with_depth_ptr_t _state = d.queue1.front(); | |
| 1776 | GraphSearchData::state_with_depth_ptr_t _endState = | ||
| 1777 | ✗ | d.addParent(_state, loopEdges[0]); | |
| 1778 | ✗ | d.solutions.push_back(_endState); | |
| 1779 | |||
| 1780 | // try connecting initial and final configurations directly | ||
| 1781 | ✗ | if (!goalDefinedByConstraints_) PathPlanner::tryConnectInitAndGoals(); | |
| 1782 | } | ||
| 1783 | |||
| 1784 | ✗ | std::vector<std::string> StatesPathFinder::constraintNamesFromSolverAtWaypoint( | |
| 1785 | std::size_t wp) { | ||
| 1786 | ✗ | assert(wp > 0 && wp <= optData_->solvers.size()); | |
| 1787 | ✗ | constraints::solver::BySubstitution& solver(optData_->solvers[wp - 1]); | |
| 1788 | ✗ | std::vector<std::string> ans; | |
| 1789 | ✗ | for (std::size_t i = 0; i < solver.constraints().size(); i++) | |
| 1790 | ✗ | ans.push_back(solver.constraints()[i]->function().name()); | |
| 1791 | ✗ | return ans; | |
| 1792 | } | ||
| 1793 | |||
| 1794 | ✗ | std::vector<std::string> StatesPathFinder::lastBuiltTransitions() const { | |
| 1795 | ✗ | std::vector<std::string> ans; | |
| 1796 | ✗ | for (const EdgePtr_t& edge : lastBuiltTransitions_) | |
| 1797 | ✗ | ans.push_back(edge->name()); | |
| 1798 | ✗ | return ans; | |
| 1799 | } | ||
| 1800 | |||
| 1801 | using core::Parameter; | ||
| 1802 | using core::ParameterDescription; | ||
| 1803 | |||
| 1804 | 1 | HPP_START_PARAMETER_DECLARATION(StatesPathFinder) | |
| 1805 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1806 | Parameter::INT, "StatesPathFinder/maxDepth", | ||
| 1807 | "Maximum number of transitions to look for.", | ||
| 1808 |
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2 | Parameter((size_type)std::numeric_limits<int>::max()))); |
| 1809 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1810 | Parameter::INT, "StatesPathFinder/maxIteration", | ||
| 1811 | "Maximum number of iterations of the Newton Raphson algorithm.", | ||
| 1812 |
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2 | Parameter((size_type)60))); |
| 1813 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1814 | Parameter::FLOAT, "StatesPathFinder/errorThreshold", | ||
| 1815 | "Error threshold of the Newton Raphson algorithm." | ||
| 1816 | "Should be at most the same as error threshold in constraint graph", | ||
| 1817 |
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2 | Parameter(1e-4))); |
| 1818 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1819 | Parameter::INT, "StatesPathFinder/nTriesUntilBacktrack", | ||
| 1820 | "Number of tries when sampling configurations before backtracking" | ||
| 1821 | "in function solveOptimizationProblem.", | ||
| 1822 |
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2 | Parameter((size_type)3))); |
| 1823 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1824 | Parameter::INT, "StatesPathFinder/maxTriesCollisionAnalysis", | ||
| 1825 | "Number of solve tries before stopping the collision analysis," | ||
| 1826 | "before the actual solving part." | ||
| 1827 | "Set to 0 to skip this part of the algorithm.", | ||
| 1828 |
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2 | Parameter((size_type)100))); |
| 1829 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1830 | Parameter::INT, "StatesPathFinder/maxTriesBuildPath", | ||
| 1831 | "Number of solutions with a given states list to try to build a" | ||
| 1832 | "continuous path from, before skipping to the next states list", | ||
| 1833 |
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2 | Parameter((size_type)5))); |
| 1834 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1835 | Parameter::FLOAT, "StatesPathFinder/innerPlannerTimeOut", | ||
| 1836 | "This will set ::timeOut accordingly in the inner" | ||
| 1837 | "planner used for building a path after intermediate" | ||
| 1838 | "configurations have been found." | ||
| 1839 | "If set to 0, no timeout: only maxIterations will be used to stop" | ||
| 1840 | "the innerPlanner if it does not find a path.", | ||
| 1841 |
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2 | Parameter(2.0))); |
| 1842 |
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1 | core::Problem::declareParameter(ParameterDescription( |
| 1843 | Parameter::INT, "StatesPathFinder/innerPlannerMaxIterations", | ||
| 1844 | "This will set ::maxIterations accordingly in the inner" | ||
| 1845 | "planner used for building a path after intermediate" | ||
| 1846 | "configurations have been found", | ||
| 1847 |
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2 | Parameter((size_type)1000))); |
| 1848 | 1 | HPP_END_PARAMETER_DECLARATION(StatesPathFinder) | |
| 1849 | } // namespace pathPlanner | ||
| 1850 | } // namespace manipulation | ||
| 1851 | } // namespace hpp | ||
| 1852 |