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<div class="title">RigidBodyPlanning.py</div> </div>
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<div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">#!/usr/bin/env python</span>
<a name="l00002"></a>00002
<a name="l00003"></a>00003 <span class="comment">######################################################################</span>
<a name="l00004"></a>00004 <span class="comment"># Software License Agreement (BSD License)</span>
<a name="l00005"></a>00005 <span class="comment">#</span>
<a name="l00006"></a>00006 <span class="comment"># Copyright (c) 2010, Rice University</span>
<a name="l00007"></a>00007 <span class="comment"># All rights reserved.</span>
<a name="l00008"></a>00008 <span class="comment">#</span>
<a name="l00009"></a>00009 <span class="comment"># Redistribution and use in source and binary forms, with or without</span>
<a name="l00010"></a>00010 <span class="comment"># modification, are permitted provided that the following conditions</span>
<a name="l00011"></a>00011 <span class="comment"># are met:</span>
<a name="l00012"></a>00012 <span class="comment">#</span>
<a name="l00013"></a>00013 <span class="comment"># * Redistributions of source code must retain the above copyright</span>
<a name="l00014"></a>00014 <span class="comment"># notice, this list of conditions and the following disclaimer.</span>
<a name="l00015"></a>00015 <span class="comment"># * Redistributions in binary form must reproduce the above</span>
<a name="l00016"></a>00016 <span class="comment"># copyright notice, this list of conditions and the following</span>
<a name="l00017"></a>00017 <span class="comment"># disclaimer in the documentation and/or other materials provided</span>
<a name="l00018"></a>00018 <span class="comment"># with the distribution.</span>
<a name="l00019"></a>00019 <span class="comment"># * Neither the name of the Rice University nor the names of its</span>
<a name="l00020"></a>00020 <span class="comment"># contributors may be used to endorse or promote products derived</span>
<a name="l00021"></a>00021 <span class="comment"># from this software without specific prior written permission.</span>
<a name="l00022"></a>00022 <span class="comment">#</span>
<a name="l00023"></a>00023 <span class="comment"># THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS</span>
<a name="l00024"></a>00024 <span class="comment"># "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT</span>
<a name="l00025"></a>00025 <span class="comment"># LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS</span>
<a name="l00026"></a>00026 <span class="comment"># FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE</span>
<a name="l00027"></a>00027 <span class="comment"># COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,</span>
<a name="l00028"></a>00028 <span class="comment"># INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span>
<a name="l00029"></a>00029 <span class="comment"># BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;</span>
<a name="l00030"></a>00030 <span class="comment"># LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER</span>
<a name="l00031"></a>00031 <span class="comment"># CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT</span>
<a name="l00032"></a>00032 <span class="comment"># LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN</span>
<a name="l00033"></a>00033 <span class="comment"># ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE</span>
<a name="l00034"></a>00034 <span class="comment"># POSSIBILITY OF SUCH DAMAGE.</span>
<a name="l00035"></a>00035 <span class="comment">######################################################################</span>
<a name="l00036"></a>00036
<a name="l00037"></a>00037 <span class="comment"># Author: Mark Moll</span>
<a name="l00038"></a>00038
<a name="l00039"></a>00039 <span class="keywordflow">try</span>:
<a name="l00040"></a>00040 <span class="keyword">from</span> ompl <span class="keyword">import</span> base <span class="keyword">as</span> ob
<a name="l00041"></a>00041 <span class="keyword">from</span> ompl <span class="keyword">import</span> geometric <span class="keyword">as</span> og
<a name="l00042"></a>00042 <span class="keywordflow">except</span>:
<a name="l00043"></a>00043 <span class="comment"># if the ompl module is not in the PYTHONPATH assume it is installed in a</span>
<a name="l00044"></a>00044 <span class="comment"># subdirectory of the parent directory called "py-bindings."</span>
<a name="l00045"></a>00045 <span class="keyword">from</span> os.path <span class="keyword">import</span> basename, abspath, dirname, join
<a name="l00046"></a>00046 <span class="keyword">import</span> sys
<a name="l00047"></a>00047 sys.path.insert(0, join(dirname(dirname(abspath(__file__))),<span class="stringliteral">'py-bindings'</span>))
<a name="l00048"></a>00048 <span class="keyword">from</span> ompl <span class="keyword">import</span> base <span class="keyword">as</span> ob
<a name="l00049"></a>00049 <span class="keyword">from</span> ompl <span class="keyword">import</span> geometric <span class="keyword">as</span> og
<a name="l00050"></a>00050
<a name="l00051"></a>00051 <span class="keyword">def </span>isStateValid(spaceInformation, state):
<a name="l00052"></a>00052 <span class="comment"># Some arbitrary condition on the state (note that thanks to</span>
<a name="l00053"></a>00053 <span class="comment"># dynamic type checking we can just call getX() and do not need</span>
<a name="l00054"></a>00054 <span class="comment"># to convert state to an SE2State.)</span>
<a name="l00055"></a>00055 <span class="keywordflow">return</span> state.getX() < .6
<a name="l00056"></a>00056
<a name="l00057"></a>00057 <span class="keyword">def </span>plan():
<a name="l00058"></a>00058 <span class="comment"># create an SE2 state space</span>
<a name="l00059"></a>00059 space = ob.SE2StateSpace()
<a name="l00060"></a>00060 <span class="comment"># set lower and upper bounds</span>
<a name="l00061"></a>00061 bounds = ob.RealVectorBounds(2)
<a name="l00062"></a>00062 bounds.setLow(-1)
<a name="l00063"></a>00063 bounds.setHigh(1)
<a name="l00064"></a>00064 space.setBounds(bounds)
<a name="l00065"></a>00065 <span class="comment"># construct an instance of space information from this state space</span>
<a name="l00066"></a>00066 si = ob.SpaceInformation(space)
<a name="l00067"></a>00067 <span class="comment"># set state validity checking for this space</span>
<a name="l00068"></a>00068 si.setStateValidityChecker(isStateValid)
<a name="l00069"></a>00069 <span class="comment"># create a random start state</span>
<a name="l00070"></a>00070 start = ob.State(space)
<a name="l00071"></a>00071 start.random()
<a name="l00072"></a>00072 <span class="comment"># create a random goal state</span>
<a name="l00073"></a>00073 goal = ob.State(space)
<a name="l00074"></a>00074 goal.random()
<a name="l00075"></a>00075 <span class="comment"># create a problem instance</span>
<a name="l00076"></a>00076 pdef = ob.ProblemDefinition(si)
<a name="l00077"></a>00077 <span class="comment"># set the start and goal states</span>
<a name="l00078"></a>00078 pdef.setStartAndGoalStates(start, goal)
<a name="l00079"></a>00079 <span class="comment"># create a planner for the defined space</span>
<a name="l00080"></a>00080 planner = og.RRTConnect(si)
<a name="l00081"></a>00081 <span class="comment"># set the problem we are trying to solve for the planner</span>
<a name="l00082"></a>00082 planner.setProblemDefinition(pdef)
<a name="l00083"></a>00083 <span class="comment"># perform setup steps for the planner</span>
<a name="l00084"></a>00084 planner.setup()
<a name="l00085"></a>00085 <span class="comment"># print the settings for this space</span>
<a name="l00086"></a>00086 <span class="keywordflow">print</span> si.settings()
<a name="l00087"></a>00087 <span class="comment"># print the problem settings</span>
<a name="l00088"></a>00088 <span class="keywordflow">print</span> pdef
<a name="l00089"></a>00089 <span class="comment"># attempt to solve the problem within one second of planning time</span>
<a name="l00090"></a>00090 solved = planner.solve(1.0)
<a name="l00091"></a>00091
<a name="l00092"></a>00092 <span class="keywordflow">if</span> solved:
<a name="l00093"></a>00093 <span class="comment"># get the goal representation from the problem definition (not the same as the goal state)</span>
<a name="l00094"></a>00094 <span class="comment"># and inquire about the found path</span>
<a name="l00095"></a>00095 path = pdef.getGoal().getSolutionPath()
<a name="l00096"></a>00096 <span class="keywordflow">print</span> <span class="stringliteral">"Found solution:\n"</span>, path
<a name="l00097"></a>00097 <span class="keywordflow">else</span>:
<a name="l00098"></a>00098 <span class="keywordflow">print</span> <span class="stringliteral">"No solution found"</span>
<a name="l00099"></a>00099
<a name="l00100"></a>00100
<a name="l00101"></a>00101 <span class="keyword">def </span>planWithSimpleSetup():
<a name="l00102"></a>00102 <span class="comment"># create an SE2 state space</span>
<a name="l00103"></a>00103 space = ob.SE2StateSpace()
<a name="l00104"></a>00104
<a name="l00105"></a>00105 <span class="comment"># set lower and upper bounds</span>
<a name="l00106"></a>00106 bounds = ob.RealVectorBounds(2)
<a name="l00107"></a>00107 bounds.setLow(-1)
<a name="l00108"></a>00108 bounds.setHigh(1)
<a name="l00109"></a>00109 space.setBounds(bounds)
<a name="l00110"></a>00110
<a name="l00111"></a>00111 <span class="comment"># create a simple setup object</span>
<a name="l00112"></a>00112 ss = og.SimpleSetup(space)
<a name="l00113"></a>00113 ss.setStateValidityChecker(isStateValid)
<a name="l00114"></a>00114
<a name="l00115"></a>00115 start = ob.State(space)
<a name="l00116"></a>00116 <span class="comment"># we can pick a random start state...</span>
<a name="l00117"></a>00117 start.random()
<a name="l00118"></a>00118 <span class="comment"># ... or set specific values</span>
<a name="l00119"></a>00119 start().setX(.5)
<a name="l00120"></a>00120
<a name="l00121"></a>00121 goal = ob.State(space)
<a name="l00122"></a>00122 <span class="comment"># we can pick a random goal state...</span>
<a name="l00123"></a>00123 goal.random()
<a name="l00124"></a>00124 <span class="comment"># ... or set specific values</span>
<a name="l00125"></a>00125 goal().setY(-.5)
<a name="l00126"></a>00126
<a name="l00127"></a>00127 ss.setStartAndGoalStates(start, goal)
<a name="l00128"></a>00128
<a name="l00129"></a>00129 <span class="comment"># this will automatically choose a default planner with</span>
<a name="l00130"></a>00130 <span class="comment"># default parameters</span>
<a name="l00131"></a>00131 solved = ss.solve(1.0)
<a name="l00132"></a>00132
<a name="l00133"></a>00133 <span class="keywordflow">if</span> solved:
<a name="l00134"></a>00134 <span class="comment"># try to shorten the path</span>
<a name="l00135"></a>00135 ss.simplifySolution()
<a name="l00136"></a>00136 <span class="comment"># print the simplified path</span>
<a name="l00137"></a>00137 <span class="keywordflow">print</span> ss.getSolutionPath()
<a name="l00138"></a>00138
<a name="l00139"></a>00139
<a name="l00140"></a>00140 <span class="keywordflow">if</span> __name__ == <span class="stringliteral">"__main__"</span>:
<a name="l00141"></a>00141 plan()
<a name="l00142"></a>00142 <span class="keywordflow">print</span> <span class="stringliteral">""</span>
<a name="l00143"></a>00143 planWithSimpleSetup()
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