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RigidBodyPlanning.py
00001 #!/usr/bin/env python
00002 
00003 ######################################################################
00004 # Software License Agreement (BSD License)
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00036 
00037 # Author: Mark Moll
00038 
00039 try:
00040     from ompl import base as ob
00041     from ompl import geometric as og
00042 except:
00043     # if the ompl module is not in the PYTHONPATH assume it is installed in a
00044     # subdirectory of the parent directory called "py-bindings."
00045     from os.path import basename, abspath, dirname, join
00046     import sys
00047     sys.path.insert(0, join(dirname(dirname(abspath(__file__))),'py-bindings'))
00048     from ompl import base as ob
00049     from ompl import geometric as og
00050 
00051 def isStateValid(spaceInformation, state):
00052     # Some arbitrary condition on the state (note that thanks to
00053     # dynamic type checking we can just call getX() and do not need
00054     # to convert state to an SE2State.)
00055     return state.getX() < .6
00056 
00057 def plan():
00058     # create an SE2 state space
00059     space = ob.SE2StateSpace()
00060     # set lower and upper bounds
00061     bounds = ob.RealVectorBounds(2)
00062     bounds.setLow(-1)
00063     bounds.setHigh(1)
00064     space.setBounds(bounds)
00065     # construct an instance of space information from this state space
00066     si = ob.SpaceInformation(space)
00067     # set state validity checking for this space
00068     si.setStateValidityChecker(isStateValid)
00069     # create a random start state
00070     start = ob.State(space)
00071     start.random()
00072     # create a random goal state
00073     goal = ob.State(space)
00074     goal.random()
00075     # create a problem instance
00076     pdef = ob.ProblemDefinition(si)
00077     # set the start and goal states
00078     pdef.setStartAndGoalStates(start, goal)
00079     # create a planner for the defined space
00080     planner = og.RRTConnect(si)
00081     # set the problem we are trying to solve for the planner
00082     planner.setProblemDefinition(pdef)
00083     # perform setup steps for the planner
00084     planner.setup()
00085     # print the settings for this space
00086     print si.settings()
00087     # print the problem settings
00088     print pdef
00089     # attempt to solve the problem within one second of planning time
00090     solved = planner.solve(1.0)
00091 
00092     if solved:
00093         # get the goal representation from the problem definition (not the same as the goal state)
00094         # and inquire about the found path
00095         path = pdef.getGoal().getSolutionPath()
00096         print "Found solution:\n", path
00097     else:
00098         print "No solution found"
00099 
00100 
00101 def planWithSimpleSetup():
00102     # create an SE2 state space
00103     space = ob.SE2StateSpace()
00104 
00105     # set lower and upper bounds
00106     bounds = ob.RealVectorBounds(2)
00107     bounds.setLow(-1)
00108     bounds.setHigh(1)
00109     space.setBounds(bounds)
00110 
00111     # create a simple setup object
00112     ss = og.SimpleSetup(space)
00113     ss.setStateValidityChecker(isStateValid)
00114 
00115     start = ob.State(space)
00116     # we can pick a random start state...
00117     start.random()
00118     # ... or set specific values
00119     start().setX(.5)
00120 
00121     goal = ob.State(space)
00122     # we can pick a random goal state...
00123     goal.random()
00124     # ... or set specific values
00125     goal().setY(-.5)
00126 
00127     ss.setStartAndGoalStates(start, goal)
00128 
00129     # this will automatically choose a default planner with
00130     # default parameters
00131     solved = ss.solve(1.0)
00132 
00133     if solved:
00134         # try to shorten the path
00135         ss.simplifySolution()
00136         # print the simplified path
00137         print ss.getSolutionPath()
00138 
00139 
00140 if __name__ == "__main__":
00141     plan()
00142     print ""
00143     planWithSimpleSetup()