| Directory: | ./ |
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| File: | include/hpp/core/configuration-shooter/gaussian.hh |
| Date: | 2024-12-13 16:14:03 |
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| 1 | // | ||
| 2 | // Copyright (c) 2018 CNRS | ||
| 3 | // Authors: Joseph Mirabel | ||
| 4 | // | ||
| 5 | |||
| 6 | // Redistribution and use in source and binary forms, with or without | ||
| 7 | // modification, are permitted provided that the following conditions are | ||
| 8 | // met: | ||
| 9 | // | ||
| 10 | // 1. Redistributions of source code must retain the above copyright | ||
| 11 | // notice, this list of conditions and the following disclaimer. | ||
| 12 | // | ||
| 13 | // 2. Redistributions in binary form must reproduce the above copyright | ||
| 14 | // notice, this list of conditions and the following disclaimer in the | ||
| 15 | // documentation and/or other materials provided with the distribution. | ||
| 16 | // | ||
| 17 | // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | ||
| 18 | // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | ||
| 19 | // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
| 20 | // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT | ||
| 21 | // HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, | ||
| 22 | // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT | ||
| 23 | // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, | ||
| 24 | // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY | ||
| 25 | // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
| 26 | // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
| 27 | // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH | ||
| 28 | // DAMAGE. | ||
| 29 | |||
| 30 | #ifndef HPP_CORE_CONFIGURATION_SHOOTER_GAUSSIAN_HH | ||
| 31 | #define HPP_CORE_CONFIGURATION_SHOOTER_GAUSSIAN_HH | ||
| 32 | |||
| 33 | #include <hpp/core/configuration-shooter.hh> | ||
| 34 | #include <hpp/pinocchio/device.hh> | ||
| 35 | #include <sstream> | ||
| 36 | |||
| 37 | namespace hpp { | ||
| 38 | namespace core { | ||
| 39 | namespace configurationShooter { | ||
| 40 | /// \addtogroup configuration_sampling | ||
| 41 | /// \{ | ||
| 42 | |||
| 43 | /// Sample configuration using a gaussian distribution around a | ||
| 44 | /// configuration. | ||
| 45 | class HPP_CORE_DLLAPI Gaussian : public ConfigurationShooter { | ||
| 46 | public: | ||
| 47 | 1 | static GaussianPtr_t create(const DevicePtr_t& robot) { | |
| 48 |
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1 | Gaussian* ptr = new Gaussian(robot); |
| 49 | 1 | GaussianPtr_t shPtr(ptr); | |
| 50 | 1 | ptr->init(shPtr); | |
| 51 | 1 | return shPtr; | |
| 52 | } | ||
| 53 | |||
| 54 | ✗ | void center(ConfigurationIn_t c) { center_ = c; } | |
| 55 | 1 | const Configuration_t& center() const { return center_; } | |
| 56 | |||
| 57 | /// Set the standard deviation proportional to a default value | ||
| 58 | /// | ||
| 59 | /// The default value is: | ||
| 60 | /// \li for vector spaces, the difference between the upper and the | ||
| 61 | /// lower bounds, | ||
| 62 | /// \li for SO(n), \f$\frac{2\pi}{\sqrt{2n-3}}\f$ on each of the | ||
| 63 | /// \f$ 2n-3 \f$ dimensions, | ||
| 64 | /// \li SE(n) is treated as \f$ R^n \times SO(n) \f$. | ||
| 65 | void sigma(const value_type& factor); | ||
| 66 | |||
| 67 | ✗ | void sigmas(vectorIn_t s) { | |
| 68 | ✗ | assert(s.size() == robot_->numberDof()); | |
| 69 | ✗ | sigmas_ = s; | |
| 70 | } | ||
| 71 | const vector_t& sigmas() const { return sigmas_; } | ||
| 72 | |||
| 73 | protected: | ||
| 74 | /// Create a gaussian distribution centered in the robot current | ||
| 75 | /// configuration. The standard deviation is computed as \c sigma(0.25) | ||
| 76 | /// \sa Gaussian::sigma | ||
| 77 | 1 | Gaussian(const DevicePtr_t& robot) | |
| 78 | 2 | : robot_(robot), | |
| 79 |
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1 | center_(robot->currentConfiguration()), |
| 80 |
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2 | sigmas_(robot->numberDof()) { |
| 81 |
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1 | sigma(1. / 4.); |
| 82 | 1 | } | |
| 83 | 1 | void init(const GaussianPtr_t& self) { | |
| 84 | 1 | ConfigurationShooter::init(self); | |
| 85 | 1 | weak_ = self; | |
| 86 | 1 | } | |
| 87 | |||
| 88 | virtual void impl_shoot(Configuration_t& q) const; | ||
| 89 | |||
| 90 | private: | ||
| 91 | const DevicePtr_t& robot_; | ||
| 92 | /// The mean value | ||
| 93 | Configuration_t center_; | ||
| 94 | /// The standard deviation | ||
| 95 | vector_t sigmas_; | ||
| 96 | |||
| 97 | GaussianWkPtr_t weak_; | ||
| 98 | }; // class Gaussian | ||
| 99 | /// \} | ||
| 100 | } // namespace configurationShooter | ||
| 101 | } // namespace core | ||
| 102 | } // namespace hpp | ||
| 103 | |||
| 104 | #endif // HPP_CORE_CONFIGURATION_SHOOTER_GAUSSIAN_HH | ||
| 105 |