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OptimizationObjective.cpp
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333 lines (279 loc) · 10.4 KB
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/*********************************************************************
* Software License Agreement (BSD License)
*
* Copyright (c) 2008, Willow Garage, Inc.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the Willow Garage nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*********************************************************************/
/* Author: Luis G. Torres, Ioan Sucan, Jonathan Gammell */
#include "ompl/base/OptimizationObjective.h"
#include "ompl/tools/config/MagicConstants.h"
#include "ompl/base/goals/GoalRegion.h"
#include "ompl/base/samplers/informed/RejectionInfSampler.h"
#include <limits>
// For std::make_shared
#include <memory>
#include <utility>
ompl::base::OptimizationObjective::OptimizationObjective(SpaceInformationPtr si) : si_(std::move(si)), threshold_(0.0)
{
}
const std::string &ompl::base::OptimizationObjective::getDescription() const
{
return description_;
}
bool ompl::base::OptimizationObjective::isSatisfied(Cost c) const
{
return isCostBetterThan(c, threshold_);
}
ompl::base::Cost ompl::base::OptimizationObjective::getCostThreshold() const
{
return threshold_;
}
void ompl::base::OptimizationObjective::setCostThreshold(Cost c)
{
threshold_ = c;
}
bool ompl::base::OptimizationObjective::isCostBetterThan(Cost c1, Cost c2) const
{
return c1.value() < c2.value();
}
bool ompl::base::OptimizationObjective::isCostEquivalentTo(Cost c1, Cost c2) const
{
// If c1 is not better than c2, and c2 is not better than c1, then they are equal
return !isCostBetterThan(c1, c2) && !isCostBetterThan(c2, c1);
}
bool ompl::base::OptimizationObjective::isFinite(Cost cost) const
{
return isCostBetterThan(cost, infiniteCost());
}
ompl::base::Cost ompl::base::OptimizationObjective::betterCost(Cost c1, Cost c2) const
{
return isCostBetterThan(c1, c2) ? c1 : c2;
}
ompl::base::Cost ompl::base::OptimizationObjective::combineCosts(Cost c1, Cost c2) const
{
return Cost(c1.value() + c2.value());
}
ompl::base::Cost ompl::base::OptimizationObjective::identityCost() const
{
return Cost(0.0);
}
ompl::base::Cost ompl::base::OptimizationObjective::infiniteCost() const
{
return Cost(std::numeric_limits<double>::infinity());
}
ompl::base::Cost ompl::base::OptimizationObjective::initialCost(const State *s) const
{
return identityCost();
}
ompl::base::Cost ompl::base::OptimizationObjective::terminalCost(const State *s) const
{
return identityCost();
}
bool ompl::base::OptimizationObjective::isSymmetric() const
{
return si_->getStateSpace()->hasSymmetricInterpolate();
}
ompl::base::Cost ompl::base::OptimizationObjective::averageStateCost(unsigned int numStates) const
{
StateSamplerPtr ss = si_->allocStateSampler();
State *state = si_->allocState();
Cost totalCost(identityCost());
for (unsigned int i = 0; i < numStates; ++i)
{
ss->sampleUniform(state);
totalCost = combineCosts(totalCost, stateCost(state));
}
si_->freeState(state);
return Cost(totalCost.value() / (double)numStates);
}
void ompl::base::OptimizationObjective::setCostToGoHeuristic(const CostToGoHeuristic &costToGo)
{
costToGoFn_ = costToGo;
}
bool ompl::base::OptimizationObjective::hasCostToGoHeuristic() const
{
return static_cast<bool>(costToGoFn_);
}
ompl::base::Cost ompl::base::OptimizationObjective::costToGo(const State *state, const Goal *goal) const
{
if (hasCostToGoHeuristic())
return costToGoFn_(state, goal);
return identityCost(); // assumes that identity < all costs
}
ompl::base::Cost ompl::base::OptimizationObjective::motionCostHeuristic(const State *s1, const State *s2) const
{
return identityCost(); // assumes that identity < all costs
}
const ompl::base::SpaceInformationPtr &ompl::base::OptimizationObjective::getSpaceInformation() const
{
return si_;
}
ompl::base::InformedSamplerPtr ompl::base::OptimizationObjective::allocInformedStateSampler(
const ProblemDefinitionPtr &probDefn, unsigned int maxNumberCalls) const
{
OMPL_INFORM("%s: No direct informed sampling scheme is defined, defaulting to rejection sampling.",
description_.c_str());
return std::make_shared<RejectionInfSampler>(probDefn, maxNumberCalls);
}
void ompl::base::OptimizationObjective::print(std::ostream &out) const
{
out << "Optimization Objective: " << description_ << " @" << this << std::endl;
out << "Optimization Threshold: " << threshold_ << std::endl;
}
ompl::base::Cost ompl::base::goalRegionCostToGo(const State *state, const Goal *goal)
{
const auto *goalRegion = goal->as<GoalRegion>();
// Ensures that all states within the goal region's threshold to
// have a cost-to-go of exactly zero.
return Cost(std::max(goalRegion->distanceGoal(state) - goalRegion->getThreshold(), 0.0));
}
ompl::base::MultiOptimizationObjective::MultiOptimizationObjective(const SpaceInformationPtr &si)
: OptimizationObjective(si), locked_(false)
{
}
ompl::base::MultiOptimizationObjective::Component::Component(OptimizationObjectivePtr obj, double weight)
: objective(std::move(obj)), weight(weight)
{
}
void ompl::base::MultiOptimizationObjective::addObjective(const OptimizationObjectivePtr &objective, double weight)
{
if (locked_)
{
throw Exception("This optimization objective is locked. No further objectives can be added.");
}
else
components_.emplace_back(objective, weight);
}
std::size_t ompl::base::MultiOptimizationObjective::getObjectiveCount() const
{
return components_.size();
}
const ompl::base::OptimizationObjectivePtr &ompl::base::MultiOptimizationObjective::getObjective(unsigned int idx) const
{
if (components_.size() > idx)
return components_[idx].objective;
throw Exception("Objective index does not exist.");
}
double ompl::base::MultiOptimizationObjective::getObjectiveWeight(unsigned int idx) const
{
if (components_.size() > idx)
return components_[idx].weight;
throw Exception("Objective index does not exist.");
}
void ompl::base::MultiOptimizationObjective::setObjectiveWeight(unsigned int idx, double weight)
{
if (components_.size() > idx)
components_[idx].weight = weight;
else
throw Exception("Objecitve index does not exist.");
}
void ompl::base::MultiOptimizationObjective::lock()
{
locked_ = true;
}
bool ompl::base::MultiOptimizationObjective::isLocked() const
{
return locked_;
}
ompl::base::Cost ompl::base::MultiOptimizationObjective::stateCost(const State *s) const
{
Cost c = identityCost();
for (const auto &component : components_)
{
c = Cost(c.value() + component.weight * (component.objective->stateCost(s).value()));
}
return c;
}
ompl::base::Cost ompl::base::MultiOptimizationObjective::motionCost(const State *s1, const State *s2) const
{
Cost c = identityCost();
for (const auto &component : components_)
{
c = Cost(c.value() + component.weight * (component.objective->motionCost(s1, s2).value()));
}
return c;
}
ompl::base::OptimizationObjectivePtr ompl::base::operator+(const OptimizationObjectivePtr &a,
const OptimizationObjectivePtr &b)
{
std::vector<MultiOptimizationObjective::Component> components;
if (a)
{
if (auto *mult = dynamic_cast<MultiOptimizationObjective *>(a.get()))
{
for (std::size_t i = 0; i < mult->getObjectiveCount(); ++i)
{
components.emplace_back(mult->getObjective(i), mult->getObjectiveWeight(i));
}
}
else
components.emplace_back(a, 1.0);
}
if (b)
{
if (auto *mult = dynamic_cast<MultiOptimizationObjective *>(b.get()))
{
for (std::size_t i = 0; i < mult->getObjectiveCount(); ++i)
{
components.emplace_back(mult->getObjective(i), mult->getObjectiveWeight(i));
}
}
else
components.emplace_back(b, 1.0);
}
auto multObj(std::make_shared<MultiOptimizationObjective>(a->getSpaceInformation()));
for (const auto &comp : components)
multObj->addObjective(comp.objective, comp.weight);
return multObj;
}
ompl::base::OptimizationObjectivePtr ompl::base::operator*(double weight, const OptimizationObjectivePtr &a)
{
std::vector<MultiOptimizationObjective::Component> components;
if (a)
{
if (auto *mult = dynamic_cast<MultiOptimizationObjective *>(a.get()))
{
for (std::size_t i = 0; i < mult->getObjectiveCount(); ++i)
{
components.emplace_back(mult->getObjective(i), weight * mult->getObjectiveWeight(i));
}
}
else
components.emplace_back(a, weight);
}
auto multObj(std::make_shared<MultiOptimizationObjective>(a->getSpaceInformation()));
for (auto const &comp : components)
multObj->addObjective(comp.objective, comp.weight);
return multObj;
}
ompl::base::OptimizationObjectivePtr ompl::base::operator*(const OptimizationObjectivePtr &a, double weight)
{
return weight * a;
}