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RigidBodyPlanning.py
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RigidBodyPlanning.py
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#!/usr/bin/env python
######################################################################
# Software License Agreement (BSD License)
#
# Copyright (c) 2010, Rice University
# 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 Rice University 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: Mark Moll
try:
from ompl import base as ob
from ompl import geometric as og
except ImportError:
# if the ompl module is not in the PYTHONPATH assume it is installed in a
# subdirectory of the parent directory called "py-bindings."
from os.path import abspath, dirname, join
import sys
sys.path.insert(0, join(dirname(dirname(abspath(__file__))), 'py-bindings'))
from ompl import base as ob
from ompl import geometric as og
def isStateValid(state):
# Some arbitrary condition on the state (note that thanks to
# dynamic type checking we can just call getX() and do not need
# to convert state to an SE2State.)
return state.getX() < .6
def planWithSimpleSetup():
# create an SE2 state space
space = ob.SE2StateSpace()
# set lower and upper bounds
bounds = ob.RealVectorBounds(2)
bounds.setLow(-1)
bounds.setHigh(1)
space.setBounds(bounds)
# create a simple setup object
ss = og.SimpleSetup(space)
ss.setStateValidityChecker(ob.StateValidityCheckerFn(isStateValid))
start = ob.State(space)
# we can pick a random start state...
start.random()
# ... or set specific values
start().setX(.5)
goal = ob.State(space)
# we can pick a random goal state...
goal.random()
# ... or set specific values
goal().setX(-.5)
ss.setStartAndGoalStates(start, goal)
# this will automatically choose a default planner with
# default parameters
solved = ss.solve(1.0)
if solved:
# try to shorten the path
ss.simplifySolution()
# print the simplified path
print(ss.getSolutionPath())
def planTheHardWay():
# create an SE2 state space
space = ob.SE2StateSpace()
# set lower and upper bounds
bounds = ob.RealVectorBounds(2)
bounds.setLow(-1)
bounds.setHigh(1)
space.setBounds(bounds)
# construct an instance of space information from this state space
si = ob.SpaceInformation(space)
# set state validity checking for this space
si.setStateValidityChecker(ob.StateValidityCheckerFn(isStateValid))
# create a random start state
start = ob.State(space)
start.random()
# create a random goal state
goal = ob.State(space)
goal.random()
# create a problem instance
pdef = ob.ProblemDefinition(si)
# set the start and goal states
pdef.setStartAndGoalStates(start, goal)
# create a planner for the defined space
planner = og.RRTConnect(si)
# set the problem we are trying to solve for the planner
planner.setProblemDefinition(pdef)
# perform setup steps for the planner
planner.setup()
# print the settings for this space
print(si.settings())
# print the problem settings
print(pdef)
# attempt to solve the problem within one second of planning time
solved = planner.solve(1.0)
if solved:
# get the goal representation from the problem definition (not the same as the goal state)
# and inquire about the found path
path = pdef.getSolutionPath()
print("Found solution:\n%s" % path)
else:
print("No solution found")
if __name__ == "__main__":
planWithSimpleSetup()
print("")
planTheHardWay()