OMPL Plugin API reference

The list of API functions below allows you to define and solve a motion planning problem with OMPL.

simOMPL.addGoalState
simOMPL.compute
simOMPL.createStateSpace
simOMPL.createTask
simOMPL.destroyStateSpace
simOMPL.destroyTask
simOMPL.drawPath
simOMPL.drawPlannerData
simOMPL.enforceBounds
simOMPL.getGoalDistance
simOMPL.getPath
simOMPL.getPathState
simOMPL.getPathStateCount
simOMPL.getPlannerData
simOMPL.getProjectedPathLength
simOMPL.getReversedPath
simOMPL.getStateSpaceDimension
simOMPL.hasApproximateSolution
simOMPL.hasExactSolution
simOMPL.hasSolution
simOMPL.interpolatePath
simOMPL.isStateValid
simOMPL.isStateWithinBounds
simOMPL.printTaskInfo
simOMPL.projectStates
simOMPL.projectionSize
simOMPL.readState
simOMPL.removeDrawingObjects
simOMPL.setAlgorithm
simOMPL.setCollisionPairs
simOMPL.setDubinsParams
simOMPL.setGoal
simOMPL.setGoalCallback
simOMPL.setGoalState
simOMPL.setGoalStates
simOMPL.setProjectionEvaluationCallback
simOMPL.setStartState
simOMPL.setStateSpace
simOMPL.setStateValidationCallback
simOMPL.setStateValidityCheckingResolution
simOMPL.setValidStateSamplerCallback
simOMPL.setVerboseLevel
simOMPL.setup
simOMPL.simplifyPath
simOMPL.solve
simOMPL.stateDistance
simOMPL.writeState

simOMPL.addGoalState

Description	Add a goal state, without clearing previously set goal state(s), if any.
Lua synopsis	simOMPL.addGoalState(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): a table of numbers, whose size must be consistent with the robot's state space specified in this task object
Lua return values	-
Python synopsis	simOMPL.addGoalState(string taskHandle, list state)
See also	simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates

simOMPL.compute

Description	Use OMPL to find a solution for this motion planning task. It is equivalent to executing: `if simOMPL.solve(task, maxTime) then simOMPL.simplifyPath(task, maxSimplificationTime) simOMPL.interpolatePath(task, stateCnt) path = simOMPL.getPath(task) end`
Lua synopsis	bool solved, float[] states=simOMPL.compute(string taskHandle, float maxTime, float maxSimplificationTime=-1.0, int stateCnt=0)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask maxTime (float): maximum time used for the path searching procedure, in seconds. maxSimplificationTime (float, default: -1.0): maximum time used for the path simplification procedure, in seconds. -1 for a default simplification procedure. stateCnt (int, default: 0): minimum number of states to be returned. 0 for a default behaviour.
Lua return values	solved (bool): true if a solution has been found. states (table of float): a table of states, representing the solution, from start to goal. States are specified linearly.
Python synopsis	bool solved, list states=simOMPL.compute(string taskHandle, float maxTime, float maxSimplificationTime=-1.0, int stateCnt=0)
See also	simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve simOMPL.drawPath simOMPL.getPath simOMPL.getPathState simOMPL.getPathStateCount simOMPL.getProjectedPathLength simOMPL.getReversedPath simOMPL.projectStates

simOMPL.createStateSpace

Description	Create a component of the state space for the motion planning problem. In case of a dubins state space, set additional parameters with simOMPL.setDubinsParams
Lua synopsis	string stateSpaceHandle=simOMPL.createStateSpace(string name, int type, int objectHandle, float[] boundsLow, float[] boundsHigh, int useForProjection, float weight=1.0, int refObjectHandle=-1)
Lua parameters	name (string): a name for this state space type (int): type of this state space component (see simOMPL.StateSpaceType) objectHandle (int): the object handle (a joint object if type is simOMPL.StateSpaceType.joint_position or .cyclic_joint_position, otherwise a shape) boundsLow (table of float): lower bounds (if type is pose, specify only the 3 position components) boundsHigh (table of float): upper bounds (if type is pose, specify only the 3 position components) useForProjection (int): if true, this object position or joint value will be used for computing a default projection weight (float, default: 1.0): the weight of this state space component, used for computing distance between states. Default value is 1.0 refObjectHandle (int, default: -1): an object handle relative to which reference frame position/orientations will be evaluated. Default value is -1, for the absolute reference frame
Lua return values	stateSpaceHandle (string): a handle to the created state space component
Python synopsis	string stateSpaceHandle=simOMPL.createStateSpace(string name, int type, int objectHandle, list boundsLow, list boundsHigh, int useForProjection, float weight=1.0, int refObjectHandle=-1)
See also	simOMPL.destroyStateSpace simOMPL.getStateSpaceDimension simOMPL.setDubinsParams simOMPL.setStateSpace

simOMPL.createTask

Description	Create a task object, used to represent the motion planning task. A task object contains informations about: collision pairs (used by the default state validity checker) state spaces start state goal state, or goal specification (e.g. pair of dummies, Lua callback, ...) various Lua callbacks (projection evaluation, state validation, goal satisfaction)
Lua synopsis	string taskHandle=simOMPL.createTask(string name)
Lua parameters	name (string): a name for this task object
Lua return values	taskHandle (string): a handle to the created task object
Python synopsis	string taskHandle=simOMPL.createTask(string name)
See also	simOMPL.addGoalState simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.destroyStateSpace

Description	Destroy the spacified state space component. Note: state space components created during simulation are automatically destroyed when simulation ends.
Lua synopsis	simOMPL.destroyStateSpace(string stateSpaceHandle)
Lua parameters	stateSpaceHandle (string): handle to state space component
Lua return values	-
Python synopsis	simOMPL.destroyStateSpace(string stateSpaceHandle)
See also	simOMPL.createStateSpace simOMPL.getStateSpaceDimension simOMPL.setDubinsParams simOMPL.setStateSpace

simOMPL.destroyTask

Description	Destroy the specified task object. Note: task objects created during simulation are automatically destroyed when simulation ends.
Lua synopsis	simOMPL.destroyTask(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	-
Python synopsis	simOMPL.destroyTask(string taskHandle)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.drawPath

Description	draw a solution path for the specified motion planning task (as lines)
Lua synopsis	int[] dwos=simOMPL.drawPath(string taskHandle, float[] path, float lineSize, float[3] color, int extraAttributes)
Lua parameters	taskHandle (string): the handle of the task path (table of float): the path, as returned by simOMPL.getPath lineSize (float): size of the line (in pixels) color (table of float, size 3): color of the lines extraAttributes (int): extra attributes to pass to sim.addDrawingObject
Lua return values	dwos (table of int): a table of handles of new drawing objects
Python synopsis	list dwos=simOMPL.drawPath(string taskHandle, list path, float lineSize, list color, int extraAttributes)
See also	simOMPL.compute simOMPL.getPath simOMPL.getPathState simOMPL.getPathStateCount simOMPL.getProjectedPathLength simOMPL.getReversedPath simOMPL.projectStates simOMPL.drawPlannerData simOMPL.removeDrawingObjects

simOMPL.drawPlannerData

Description	draw planner data (graph) extracted from the specified motion planning task
Lua synopsis	int[] dwos=simOMPL.drawPlannerData(string taskHandle, float pointSize, float lineSize, float[3] color, float[3] startColor, float[3] goalColor)
Lua parameters	taskHandle (string): handle of the task pointSize (float): size of nodes (in meters) lineSize (float): size of lines (in pixels) color (table of float, size 3): color of nodes and lines startColor (table of float, size 3): color of start nodes goalColor (table of float, size 3): color of goal nodes
Lua return values	dwos (table of int): a table of handles of new drawing objects
Python synopsis	list dwos=simOMPL.drawPlannerData(string taskHandle, float pointSize, float lineSize, list color, list startColor, list goalColor)
See also	simOMPL.drawPath simOMPL.removeDrawingObjects

simOMPL.enforceBounds

Description	Bring the state within the bounds of the state space.
Lua synopsis	float[] state=simOMPL.enforceBounds(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): state vector
Lua return values	state (table of float): state vector
Python synopsis	list state=simOMPL.enforceBounds(string taskHandle, list state)
See also	simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.readState simOMPL.stateDistance simOMPL.writeState

simOMPL.getGoalDistance

Description	Get the distance to the desired goal for the top solution.
Lua synopsis	float distance=simOMPL.getGoalDistance(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	distance (float): distance to the desired goal for the top solution, or -1.0 if there are no solutions available
Python synopsis	float distance=simOMPL.getGoalDistance(string taskHandle)
See also	simOMPL.compute simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve

simOMPL.getPath

Description	Return the top solution path, if one is found. The top path is the shortest one that was found, preference being given to solutions that are not approximate.
Lua synopsis	float[] states=simOMPL.getPath(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	states (table of float): a table of states, representing the solution, from start to goal. States are specified linearly.
Python synopsis	list states=simOMPL.getPath(string taskHandle)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve simOMPL.compute simOMPL.drawPath simOMPL.getPathState simOMPL.getPathStateCount simOMPL.getProjectedPathLength simOMPL.getReversedPath simOMPL.projectStates

simOMPL.getPathState

Description	extract the state at specified index from the given path
Lua synopsis	float[] state=simOMPL.getPathState(string taskHandle, float[] path, int index)
Lua parameters	taskHandle (string): the handle of the task path (table of float): the path, as returned by simOMPL.getPath index (int): the index, starting from 1
Lua return values	state (table of float): a state extracted from the path
Python synopsis	list state=simOMPL.getPathState(string taskHandle, list path, int index)
See also	simOMPL.compute simOMPL.drawPath simOMPL.getPath simOMPL.getPathStateCount simOMPL.getProjectedPathLength simOMPL.getReversedPath simOMPL.projectStates simOMPL.enforceBounds simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.readState simOMPL.stateDistance simOMPL.writeState

simOMPL.getPathStateCount

Description	get the number of states in the given path
Lua synopsis	int count=simOMPL.getPathStateCount(string taskHandle, float[] path)
Lua parameters	taskHandle (string): the handle of the task path (table of float): the path, as returned by simOMPL.getPath
Lua return values	count (int): the number of states in the path
Python synopsis	int count=simOMPL.getPathStateCount(string taskHandle, list path)
See also	simOMPL.compute simOMPL.drawPath simOMPL.getPath simOMPL.getPathState simOMPL.getProjectedPathLength simOMPL.getReversedPath simOMPL.projectStates simOMPL.enforceBounds simOMPL.getPathState simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.readState simOMPL.stateDistance simOMPL.writeState

simOMPL.getPlannerData

Description	Get planner data for this motion planning task. Data is represented as a graph. For each graph vertex, a state and a tag are returned. A list of edges is returned as well, as pairs of vertex indices, describing connectivity of vertices. Some vertices are marked start or goal.
Lua synopsis	float[] states, int[] tags, float[] tagsReal, int[] edges, float[] edgeWeights, int[] startVertices, int[] goalVertices=simOMPL.getPlannerData(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask.
Lua return values	states (table of float): a table of states, representing the configurations in the constructed search graph. States are specified linearly. tags (table of int): a table of tags (one integer for every vertex) tagsReal (table of float): a table of tags (one float for every vertex) edges (table of int): the pairs of vertex indices describing vertex connectivity edgeWeights (table of float): the weight (cost) associated to each edge startVertices (table of int): the indices of vertices marked 'start' goalVertices (table of int): the indices of vertices marked 'goal'
Python synopsis	list states, list tags, list tagsReal, list edges, list edgeWeights, list startVertices, list goalVertices=simOMPL.getPlannerData(string taskHandle)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve

simOMPL.getProjectedPathLength

Description	get the length of the path projected onto the default projection
Lua synopsis	simOMPL.getProjectedPathLength(string taskHandle, float[] path)
Lua parameters	taskHandle (string): the handle of the task path (table of float): the path, as returned by simOMPL.getPath
Lua return values	-
Python synopsis	simOMPL.getProjectedPathLength(string taskHandle, list path)
See also	simOMPL.compute simOMPL.drawPath simOMPL.getPath simOMPL.getPathState simOMPL.getPathStateCount simOMPL.getReversedPath simOMPL.projectStates simOMPL.projectStates simOMPL.projectionSize simOMPL.setProjectionEvaluationCallback

simOMPL.getReversedPath

Description	reverse the given path
Lua synopsis	float[] reversedPath=simOMPL.getReversedPath(string taskHandle, float[] path)
Lua parameters	taskHandle (string): the handle of the task path (table of float): the path, as returned by simOMPL.getPath
Lua return values	reversedPath (table of float): the reversed path
Python synopsis	list reversedPath=simOMPL.getReversedPath(string taskHandle, list path)
See also	simOMPL.compute simOMPL.drawPath simOMPL.getPath simOMPL.getPathState simOMPL.getPathStateCount simOMPL.getProjectedPathLength simOMPL.projectStates

simOMPL.getStateSpaceDimension

Description	Get the dimension of the state space, i.e. the number of elements of a state.
Lua synopsis	int dim=simOMPL.getStateSpaceDimension(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	dim (int): dimension of the state space
Python synopsis	int dim=simOMPL.getStateSpaceDimension(string taskHandle)
See also	simOMPL.createStateSpace simOMPL.destroyStateSpace simOMPL.setDubinsParams simOMPL.setStateSpace

simOMPL.hasApproximateSolution

Description	Return true if the top found solution is approximate. An approximate solution does not actually reach the desired goal, but hopefully is closer to it.
Lua synopsis	bool result=simOMPL.hasApproximateSolution(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	result (bool): true if the top found solution is approximate
Python synopsis	bool result=simOMPL.hasApproximateSolution(string taskHandle)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve

simOMPL.hasExactSolution

Description	Returns true if an exact solution path has been found. Specifically returns hasSolution() and not hasApproximateSolution()
Lua synopsis	bool result=simOMPL.hasExactSolution(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	result (bool): true if an exact solution path has been found
Python synopsis	bool result=simOMPL.hasExactSolution(string taskHandle)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve

simOMPL.hasSolution

Description	Returns true if a solution path has been found (could be approximate).
Lua synopsis	bool result=simOMPL.hasSolution(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	result (bool): true if a solution path has been found (could be approximate)
Python synopsis	bool result=simOMPL.hasSolution(string taskHandle)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve

simOMPL.interpolatePath

Description	Interpolate the path found by planner to obtain a minimum number of states.
Lua synopsis	simOMPL.interpolatePath(string taskHandle, int stateCnt=0)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask stateCnt (int, default: 0): minimum number of states to be returned. 0 for a default behaviour.
Lua return values	-
Python synopsis	simOMPL.interpolatePath(string taskHandle, int stateCnt=0)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.setAlgorithm simOMPL.simplifyPath simOMPL.solve

simOMPL.isStateValid

Description	Check if the specified state is valid. If a state validation callback has been specified, that will be used to determine the validity of the state, otherwise the default state validation method will be used.
Lua synopsis	bool valid=simOMPL.isStateValid(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): state vector
Lua return values	valid (bool): true if the state is valid
Python synopsis	bool valid=simOMPL.isStateValid(string taskHandle, list state)
See also	simOMPL.enforceBounds simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.readState simOMPL.stateDistance simOMPL.writeState

simOMPL.isStateWithinBounds

Description	Check if the specified state is inside the bounding box.
Lua synopsis	bool valid=simOMPL.isStateWithinBounds(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): state vector
Lua return values	valid (bool): true if the state is within the bounding box
Python synopsis	bool valid=simOMPL.isStateWithinBounds(string taskHandle, list state)
See also	simOMPL.enforceBounds simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.projectStates simOMPL.readState simOMPL.stateDistance simOMPL.writeState

simOMPL.printTaskInfo

Description	Print a summary of the specified task object. Useful for debugging and submitting bug reports.
Lua synopsis	simOMPL.printTaskInfo(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	-
Python synopsis	simOMPL.printTaskInfo(string taskHandle)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.projectStates

Description	Project a state using the task's projection evaluation routine. If multiple states are specified (e.g. a path) multiple projections will be returned.
Lua synopsis	float[] projection=simOMPL.projectStates(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): state vector(s)
Lua return values	projection (table of float): state projection vector(s)
Python synopsis	list projection=simOMPL.projectStates(string taskHandle, list state)
See also	simOMPL.enforceBounds simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.readState simOMPL.stateDistance simOMPL.writeState simOMPL.getProjectedPathLength simOMPL.projectionSize simOMPL.setProjectionEvaluationCallback simOMPL.compute simOMPL.drawPath simOMPL.getPath simOMPL.getPathState simOMPL.getPathStateCount simOMPL.getProjectedPathLength simOMPL.getReversedPath

simOMPL.projectionSize

Description	return the dimension of the projection
Lua synopsis	int size=simOMPL.projectionSize(string taskHandle)
Lua parameters	taskHandle (string): the handle of the task
Lua return values	size (int): of the projection
Python synopsis	int size=simOMPL.projectionSize(string taskHandle)
See also	simOMPL.getProjectedPathLength simOMPL.projectStates simOMPL.setProjectionEvaluationCallback

simOMPL.readState

Description	Read a state vector from current simulator state.
Lua synopsis	float[] state=simOMPL.readState(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	state (table of float): state vector
Python synopsis	list state=simOMPL.readState(string taskHandle)
See also	simOMPL.enforceBounds simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.stateDistance simOMPL.writeState

simOMPL.removeDrawingObjects

Description	remove the drawing objects created with related functions
Lua synopsis	simOMPL.removeDrawingObjects(string taskHandle, int[] dwos)
Lua parameters	taskHandle (string): handle of the task dwos (table of int): table of handles to drawing objects, as returned by the functions
Lua return values	-
Python synopsis	simOMPL.removeDrawingObjects(string taskHandle, list dwos)
See also	simOMPL.drawPath simOMPL.drawPlannerData

simOMPL.setAlgorithm

Description	Set the search algorithm for the specified task. Default algorithm used is KPIECE1.
Lua synopsis	simOMPL.setAlgorithm(string taskHandle, int algorithm)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask algorithm (int): see simOMPL.Algorithm
Lua return values	-
Python synopsis	simOMPL.setAlgorithm(string taskHandle, int algorithm)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.simplifyPath simOMPL.solve

simOMPL.setCollisionPairs

Description	Set the collision pairs for the specified task object.
Lua synopsis	simOMPL.setCollisionPairs(string taskHandle, int[] collisionPairHandles)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask collisionPairHandles (table of int): a table containing 2 entity handles for each collision pair. A collision pair is represented by a collider and a collidee, that will be tested against each other. The collider can be an object or a collection handle. The collidee can be an object or collection handle, or sim_handle_all, in which case the collider will be checked agains all other collidable objects in the scene.
Lua return values	-
Python synopsis	simOMPL.setCollisionPairs(string taskHandle, list collisionPairHandles)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setDubinsParams

Description	Set extra state space parameters of a dubins state space.
Lua synopsis	simOMPL.setDubinsParams(string stateSpaceHandle, float turningRadius, bool isSymmetric)
Lua parameters	stateSpaceHandle (string): handle to state space component turningRadius (float): turning radius isSymmetric (bool): true if it is symmetric, otherwise false
Lua return values	-
Python synopsis	simOMPL.setDubinsParams(string stateSpaceHandle, float turningRadius, bool isSymmetric)
See also	simOMPL.createStateSpace simOMPL.destroyStateSpace simOMPL.getStateSpaceDimension simOMPL.setStateSpace

simOMPL.setGoal

Description	Set the goal for the specificed task object by a dummy pair. One of the two dummies is part of the robot. The other dummy is fixed in the environment. When the task is solved, the position or pose of the two dummies will (approximatively) be the same. Dummy-dummy distances are relative to an optional reference dummy, and are evaluated using an optional metric
Lua synopsis	simOMPL.setGoal(string taskHandle, int robotDummy, int goalDummy, float tolerance=0.001f, float[] metric={1.0, 1.0, 1.0, 0.1}, int refDummy=-1)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask robotDummy (int): a dummy attached to the robot goalDummy (int): a dummy fixed in the environment, representing the goal pose/position tolerance (float, default: 0.001f): tolerated dummy-dummy distance metric (table of float, default: {1.0, 1.0, 1.0, 0.1}): a metric (x,y,z,angle) used to evaluate the dummy-dummy distance refDummy (int, default: -1): an reference dummy, relative to which the metric will be used
Lua return values	-
Python synopsis	simOMPL.setGoal(string taskHandle, int robotDummy, int goalDummy, float tolerance=0.001f, list metric={1.0, 1.0, 1.0, 0.1}, int refDummy=-1)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup simOMPL.addGoalState simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates

simOMPL.setGoalCallback

Description	Set a custom goal callback for the specified task. See goalCallback for the arguments and the return values of the callback. If a distance to the goal is not known, a constant value can be used, but the performance of the algorithm will be worse.
Lua synopsis	simOMPL.setGoalCallback(string taskHandle, string callback)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask callback (string): name of the Lua callback
Lua return values	-
Python synopsis	simOMPL.setGoalCallback(string taskHandle, string callback)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup simOMPL.addGoalState simOMPL.setGoal simOMPL.setGoalState simOMPL.setGoalStates

simOMPL.setGoalState

Description	Set the goal state for the specified task object.
Lua synopsis	simOMPL.setGoalState(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): a table of numbers, whose size must be consistent with the robot's state space specified in this task object
Lua return values	-
Python synopsis	simOMPL.setGoalState(string taskHandle, list state)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup simOMPL.addGoalState simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalStates

simOMPL.setGoalStates

Description	set multiple goal states at once, equivalent to calling simOMPL.setGoalState, simOMPL.addGoalState, simOMPL.addGoalState...
Lua synopsis	simOMPL.setGoalStates(string taskHandle, table states)
Lua parameters	taskHandle (string): the handle of the task states (table, size 1..*): a table of tables, one element for each goal state
Lua return values	-
Python synopsis	simOMPL.setGoalStates(string taskHandle, list states)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup simOMPL.addGoalState simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState

simOMPL.setProjectionEvaluationCallback

Description	Set a custom projection evaluation. See projectionEvaluationCallback for the arguments and the return values of the callback.
Lua synopsis	simOMPL.setProjectionEvaluationCallback(string taskHandle, string callback, int projectionSize)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask callback (string): name of the Lua callback projectionSize (int): size of the projection (usually 2 or 3)
Lua return values	-
Python synopsis	simOMPL.setProjectionEvaluationCallback(string taskHandle, string callback, int projectionSize)
See also	simOMPL.getProjectedPathLength simOMPL.projectStates simOMPL.projectionSize simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setStartState

Description	Set the start state for the specified task object.
Lua synopsis	simOMPL.setStartState(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): a table of numbers, whose size must be consistent with the robot's state space specified in this task object
Lua return values	-
Python synopsis	simOMPL.setStartState(string taskHandle, list state)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setStateSpace

Description	Set the state space of this task object.
Lua synopsis	simOMPL.setStateSpace(string taskHandle, string[] stateSpaceHandles)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask stateSpaceHandles (table of string): a table of handles to state space components, created with simOMPL.createStateSpace
Lua return values	-
Python synopsis	simOMPL.setStateSpace(string taskHandle, list stateSpaceHandles)
See also	simOMPL.createStateSpace simOMPL.destroyStateSpace simOMPL.getStateSpaceDimension simOMPL.setDubinsParams simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setStateValidationCallback

Description	Set a custom state validation. See stateValidationCallback for the arguments and the return values of the callback. By default state validation is performed by collision checking, between robot's collision objects and environment's objects. By specifying a custom state validation, it is possible to perform any arbitrary check on a state to determine wether it is valid or not.
Lua synopsis	simOMPL.setStateValidationCallback(string taskHandle, string callback)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask callback (string): name of the Lua callback
Lua return values	-
Python synopsis	simOMPL.setStateValidationCallback(string taskHandle, string callback)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setStateValidityCheckingResolution

Description	Set the resolution of state validity checking, expressed as fraction of state space's extent. Default resolution is 0.01 which is 1% of the state space's extent.
Lua synopsis	simOMPL.setStateValidityCheckingResolution(string taskHandle, float resolution)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask resolution (float): resolution of state validity checking, expressed as fraction of state space's extent
Lua return values	-
Python synopsis	simOMPL.setStateValidityCheckingResolution(string taskHandle, float resolution)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setValidStateSamplerCallback

Description	Set a valid state sampler callbacks for the specified task. See validStateSamplerCallback and validStateSamplerCallbackNear for the arguments and the return values of the callbacks. The valid state sampler callbacks must generate valid states.
Lua synopsis	simOMPL.setValidStateSamplerCallback(string taskHandle, string callback, string callbackNear)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask callback (string): the name of the Lua callback for sampling a state callbackNear (string): the name of the Lua callback for sampling near a given state within the given distance
Lua return values	-
Python synopsis	simOMPL.setValidStateSamplerCallback(string taskHandle, string callback, string callbackNear)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setVerboseLevel simOMPL.setup

simOMPL.setVerboseLevel

Description	Set the verbosity level for messages printed to application console.
Lua synopsis	simOMPL.setVerboseLevel(string taskHandle, int verboseLevel)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask verboseLevel (int): level of verbosity (positive integer), 0 to suppress any message
Lua return values	-
Python synopsis	simOMPL.setVerboseLevel(string taskHandle, int verboseLevel)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setup

simOMPL.setup

Description	Setup the OMPL classes with the information contained in the task.
Lua synopsis	simOMPL.setup(string taskHandle)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask
Lua return values	-
Python synopsis	simOMPL.setup(string taskHandle)
See also	simOMPL.addGoalState simOMPL.createTask simOMPL.destroyTask simOMPL.printTaskInfo simOMPL.setAlgorithm simOMPL.setCollisionPairs simOMPL.setGoal simOMPL.setGoalCallback simOMPL.setGoalState simOMPL.setGoalStates simOMPL.setProjectionEvaluationCallback simOMPL.setStartState simOMPL.setStateSpace simOMPL.setStateValidationCallback simOMPL.setStateValidityCheckingResolution simOMPL.setValidStateSamplerCallback simOMPL.setVerboseLevel

simOMPL.simplifyPath

Description	Simplify the path found by planner.
Lua synopsis	simOMPL.simplifyPath(string taskHandle, float maxSimplificationTime=-1.0)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask maxSimplificationTime (float, default: -1.0): maximum time used for the path simplification procedure, in seconds. -1 for a default simplification procedure.
Lua return values	-
Python synopsis	simOMPL.simplifyPath(string taskHandle, float maxSimplificationTime=-1.0)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.solve

simOMPL.solve

Description	Run the planning algorithm to search for a solution.
Lua synopsis	bool solved=simOMPL.solve(string taskHandle, float maxTime)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask maxTime (float): maximum time used for the path searching procedure, in seconds.
Lua return values	solved (bool): true if a solution is found.
Python synopsis	bool solved=simOMPL.solve(string taskHandle, float maxTime)
See also	simOMPL.compute simOMPL.getGoalDistance simOMPL.getPath simOMPL.getPlannerData simOMPL.hasApproximateSolution simOMPL.hasExactSolution simOMPL.hasSolution simOMPL.interpolatePath simOMPL.setAlgorithm simOMPL.simplifyPath

simOMPL.stateDistance

Description	Compute the distanbce between two states.
Lua synopsis	float distance=simOMPL.stateDistance(string taskHandle, float[] a, float[] b)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask a (table of float): state vector b (table of float): state vector
Lua return values	distance (float): computed distance
Python synopsis	float distance=simOMPL.stateDistance(string taskHandle, list a, list b)
See also	simOMPL.enforceBounds simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.readState simOMPL.writeState

simOMPL.writeState

Description	Write the specified state to simulator
Lua synopsis	simOMPL.writeState(string taskHandle, float[] state)
Lua parameters	taskHandle (string): a handle to a task object created with simOMPL.createTask state (table of float): state vector
Lua return values	-
Python synopsis	simOMPL.writeState(string taskHandle, list state)
See also	simOMPL.enforceBounds simOMPL.getPathState simOMPL.getPathStateCount simOMPL.isStateValid simOMPL.isStateWithinBounds simOMPL.projectStates simOMPL.readState simOMPL.stateDistance

Constants

Constants used in the various functions. Refer to each constant using enumName.constantName, i.e. simUI.curve_type.xy for xy constant in simUI.curve_type enum.

simOMPL.Algorithm

BiTRRT

BITstar

BKPIECE1

CForest

EST

FMT

KPIECE1

LazyPRM

LazyPRMstar

LazyRRT

LBKPIECE1

LBTRRT

PDST

PRM

PRMstar

RRT

RRTConnect

RRTstar

SBL

SPARS

SPARStwo

STRIDE

TRRT

simOMPL.StateSpaceType

position2d

pose2d

position3d

pose3d

joint_position

dubins

cyclic_joint_position

Script functions

Script functions are used to call some lua code from the plugin side (tipically used for event handlers).

goalCallback

Description	Callback for checking if the goal is satisfied.
Lua synopsis	bool satisfied, float distance=simOMPL.goalCallback(float[] state)
Lua parameters	state (table of float): the state to test for goal satisfaction
Lua return values	satisfied (bool): true if satisfied, false otherwise distance (float): distance to goal, if it is known. A constant value can be returned otherwise, but the performance of the algorithm will be worse.
Python synopsis	bool satisfied, float distance=simOMPL.goalCallback(list state)
See also

projectionEvaluationCallback

Description	Callback for computing a (euclidean) projection of states.
Lua synopsis	float[] projection=simOMPL.projectionEvaluationCallback(float[] state)
Lua parameters	state (table of float): the state to compute the projection for
Lua return values	projection (table of float): projected state, usualy of size 2 or 3, representing a point in plane or space.
Python synopsis	list projection=simOMPL.projectionEvaluationCallback(list state)
See also

stateValidationCallback

Description	Callback for checking the validity of states.
Lua synopsis	bool valid=simOMPL.stateValidationCallback(float[] state)
Lua parameters	state (table of float): the state to compute the projection for
Lua return values	valid (bool): true if valid, false otherwise
Python synopsis	bool valid=simOMPL.stateValidationCallback(list state)
See also

validStateSamplerCallback

Description	Callback for sampling valid states from the state space.
Lua synopsis	float[] sampledState=simOMPL.validStateSamplerCallback()
Lua parameters	-
Lua return values	sampledState (table of float): a valid state
Python synopsis	list sampledState=simOMPL.validStateSamplerCallback()
See also

validStateSamplerCallbackNear

Description	Callback for sampling valid states in the proximity of a given state, within a certain distance.
Lua synopsis	float[] sampledState=simOMPL.validStateSamplerCallbackNear(float[] state, float distance)
Lua parameters	state (table of float): the center state distance (float): distance bound
Lua return values	sampledState (table of float): a valid state
Python synopsis	list sampledState=simOMPL.validStateSamplerCallbackNear(list state, float distance)
See also