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/////////////////////////////////////////////////////////////////////////////// |
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// BSD 3-Clause License |
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// |
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// Copyright (C) 2019-2023, LAAS-CNRS, Heriot-Watt University |
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// Copyright note valid unless otherwise stated in individual files. |
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// All rights reserved. |
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/////////////////////////////////////////////////////////////////////////////// |
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#include <example-robot-data/path.hpp> |
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#include <pinocchio/parsers/srdf.hpp> |
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#include <pinocchio/parsers/urdf.hpp> |
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#include "crocoddyl/core/solvers/fddp.hpp" |
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#include "crocoddyl/core/utils/callbacks.hpp" |
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#include "crocoddyl/core/utils/timer.hpp" |
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#include "crocoddyl/multibody/utils/quadruped-gaits.hpp" |
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int main(int argc, char* argv[]) { |
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bool CALLBACKS = false; |
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unsigned int T = 5e3; // number of trials |
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unsigned int MAXITER = 1; |
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if (argc > 1) { |
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T = atoi(argv[1]); |
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} |
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pinocchio::Model model; |
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pinocchio::urdf::buildModel(EXAMPLE_ROBOT_DATA_MODEL_DIR |
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"/hyq_description/robots/hyq_no_sensors.urdf", |
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pinocchio::JointModelFreeFlyer(), model); |
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pinocchio::srdf::loadReferenceConfigurations( |
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model, EXAMPLE_ROBOT_DATA_MODEL_DIR "/hyq_description/srdf/hyq.srdf", |
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false); |
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crocoddyl::SimpleQuadrupedGaitProblem gait(model, "lf_foot", "rf_foot", |
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"lh_foot", "rh_foot"); |
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const Eigen::VectorXd& x0 = gait.get_defaultState(); |
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// Walking gait_phase |
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const double stepLength(0.25), stepHeight(0.25), timeStep(1e-2); |
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const unsigned int stepKnots(25), supportKnots(2); |
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// DDP Solver |
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boost::shared_ptr<crocoddyl::ShootingProblem> problem = |
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gait.createWalkingProblem(x0, stepLength, stepHeight, timeStep, stepKnots, |
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supportKnots); |
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crocoddyl::SolverFDDP solver(problem); |
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if (CALLBACKS) { |
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std::vector<boost::shared_ptr<crocoddyl::CallbackAbstract> > cbs; |
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cbs.push_back(boost::make_shared<crocoddyl::CallbackVerbose>()); |
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solver.setCallbacks(cbs); |
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} |
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// Initial State |
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const std::size_t N = solver.get_problem()->get_T(); |
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std::vector<Eigen::VectorXd> xs(N, x0); |
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std::vector<Eigen::VectorXd> us = problem->quasiStatic_xs(xs); |
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xs.push_back(x0); |
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std::cout << "NQ: " |
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<< solver.get_problem()->get_terminalModel()->get_state()->get_nq() |
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<< std::endl; |
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std::cout << "Number of nodes: " << N << std::endl; |
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// Solving the optimal control problem |
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Eigen::ArrayXd duration(T); |
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for (unsigned int i = 0; i < T; ++i) { |
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crocoddyl::Timer timer; |
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solver.solve(xs, us, MAXITER, false, 0.1); |
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duration[i] = timer.get_duration(); |
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} |
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double avrg_duration = duration.mean(); |
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double min_duration = duration.minCoeff(); |
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double max_duration = duration.maxCoeff(); |
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std::cout << " FDDP.solve [ms]: " << avrg_duration << " (" << min_duration |
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<< "-" << max_duration << ")" << std::endl; |
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// Running calc |
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for (unsigned int i = 0; i < T; ++i) { |
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crocoddyl::Timer timer; |
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problem->calc(xs, us); |
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duration[i] = timer.get_duration(); |
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} |
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avrg_duration = duration.sum() / T; |
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min_duration = duration.minCoeff(); |
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max_duration = duration.maxCoeff(); |
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std::cout << " ShootingProblem.calc [ms]: " << avrg_duration << " (" |
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<< min_duration << "-" << max_duration << ")" << std::endl; |
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// Running calcDiff |
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for (unsigned int i = 0; i < T; ++i) { |
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crocoddyl::Timer timer; |
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problem->calcDiff(xs, us); |
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duration[i] = timer.get_duration(); |
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} |
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avrg_duration = duration.sum() / T; |
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min_duration = duration.minCoeff(); |
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max_duration = duration.maxCoeff(); |
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std::cout << " ShootingProblem.calcDiff [ms]: " << avrg_duration << " (" |
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<< min_duration << "-" << max_duration << ")" << std::endl; |
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} |
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