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00001 /********************************************************************* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Copyright (c) 2010, Willow Garage, Inc. 00005 * All rights reserved. 00006 * 00007 * Redistribution and use in source and binary forms, with or without 00008 * modification, are permitted provided that the following conditions 00009 * are met: 00010 * 00011 * * Redistributions of source code must retain the above copyright 00012 * notice, this list of conditions and the following disclaimer. 00013 * * Redistributions in binary form must reproduce the above 00014 * copyright notice, this list of conditions and the following 00015 * disclaimer in the documentation and/or other materials provided 00016 * with the distribution. 00017 * * Neither the name of the Willow Garage nor the names of its 00018 * contributors may be used to endorse or promote products derived 00019 * from this software without specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00022 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00023 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00024 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00025 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00026 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00027 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00028 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00029 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00030 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00031 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00032 * POSSIBILITY OF SUCH DAMAGE. 00033 *********************************************************************/ 00034 00035 // Author(s): Peter Brook 00036 00037 #include <boost/foreach.hpp> 00038 00039 #include "probabilistic_grasp_planner/distribution_evaluator.h" 00040 #include "probabilistic_grasp_planner/probabilistic_planner_tools.h" 00041 #include "probabilistic_grasp_planner/grasp_success_probability_computer.h" 00042 #include "probabilistic_grasp_planner/grasp_regression_evaluator.h" 00043 00044 namespace probabilistic_grasp_planner { 00045 00046 double GraspRegressionEvaluator::estimateProbability(const GraspWithMetadata &grasp) const 00047 { 00048 NormalDistributionEvaluator evaluator(position_bandwidth_, orientation_bandwidth_); 00049 evaluator.reset_normalization_term(); 00050 00051 double probability = 0.0; 00052 00053 const GraspWithMetadata* closest_grasp = NULL; 00054 double closest_dist = 0.0; 00055 00056 double cartesian_dist, rotation_dist; 00057 00058 BOOST_FOREACH(const GraspWithMetadata &grasp_for_object, grasps_) 00059 { 00060 // Find closest grasp 00061 if (closest_grasp==NULL) 00062 { 00063 closest_grasp = &grasp_for_object; 00064 00065 grasp.getDistance(grasp_for_object, cartesian_dist, rotation_dist); 00066 00067 closest_dist = sqrt(pow(position_bandwidth_*cartesian_dist,2) + 00068 pow(orientation_bandwidth_*rotation_dist,2)); 00069 } 00070 00071 grasp.getDistance(grasp_for_object, cartesian_dist, rotation_dist); 00072 00073 double this_dist = sqrt(pow(position_bandwidth_*cartesian_dist,2) + 00074 pow(orientation_bandwidth_*rotation_dist,2)); 00075 00076 if (this_dist < closest_dist) 00077 { 00078 closest_grasp = &grasp_for_object; 00079 closest_dist = this_dist; 00080 } 00081 00082 //Add the weighted contribution from grasp_for_object to grasp's probability 00083 double p_dens = evaluator.evaluate(grasp_for_object, grasp); 00084 double grasp_probability = simple_computer_->getProbability(grasp_for_object); 00085 probability += p_dens*grasp_probability; 00086 } 00087 00088 // If this is false, then all of the probabilities are zero so we should return that directly 00089 if (evaluator.get_normalization_term() != 0.0) 00090 { 00091 probability /= evaluator.get_normalization_term(); 00092 00093 double p_dens = evaluator.evaluate(*closest_grasp, grasp); 00094 double grasp_probability = simple_computer_->getProbability(*closest_grasp); 00095 double probability_from_closest_grasp = p_dens*grasp_probability; 00096 00097 return std::min(probability, probability_from_closest_grasp); 00098 } 00099 else { 00100 return 0.0; 00101 } 00102 } 00103 00104 } // end namespace