ConstrainedPlanningImplicitChain.ChainConstraint Class Reference

Inheritance diagram for ConstrainedPlanningImplicitChain.ChainConstraint:

Classes
class	Wall

Public Member Functions
def	__init__ (self, links, obstacles=0, extra=1)
def	function (self, x, out)
def	jacobian (self, x, out)
def	isValid (self, state)
def	createSpace (self)
def	getStartAndGoalStates (self)
def	getProjection (self, space)
def	dump (self, outfile)
def	addBenchmarkParameters (self, bench)
Public Member Functions inherited from ompl::base::Constraint
	Constraint (const unsigned int ambientDim, const unsigned int coDim, double tolerance=magic::CONSTRAINT_PROJECTION_TOLERANCE)
	Constructor. The dimension of the ambient configuration space as well as the dimension of the function's output need to be specified (the co-dimension of the constraint manifold). I.E., for a sphere constraint function in.
virtual void	function (const State *state, Eigen::Ref< Eigen::VectorXd > out) const
	Compute the constraint function at state. Result is returned in out, which should be allocated to size coDim.
virtual void	function (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::Ref< Eigen::VectorXd > out) const =0
	Compute the constraint function at x. Result is returned in out, which should be allocated to size coDim.
virtual void	jacobian (const State *state, Eigen::Ref< Eigen::MatrixXd > out) const
	Compute the Jacobian of the constraint function at state. Result is returned in out, which should be allocated to size coDim by ambientDim. Default implementation performs the differentiation numerically with a seven-point central difference stencil. It is best to provide an analytic formulation.
virtual void	jacobian (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::Ref< Eigen::MatrixXd > out) const
	Compute the Jacobian of the constraint function at x. Result is returned in out, which should be allocated to size coDim by ambientDim. Default implementation performs the differentiation numerically with a seven-point central difference stencil. It is best to provide an analytic formulation.
virtual bool	project (State *state) const
	Project a state state given the constraints. If a valid projection cannot be found, this method will return false. Even if this method fails, state will be modified.
virtual bool	project (Eigen::Ref< Eigen::VectorXd > x) const
	Project a state x given the constraints. If a valid projection cannot be found, this method will return false.
virtual double	distance (const State *state) const
	Returns the distance of state to the constraint manifold.
virtual double	distance (const Eigen::Ref< const Eigen::VectorXd > &x) const
	Returns the distance of x to the constraint manifold.
virtual bool	isSatisfied (const State *state) const
	Check whether a state state satisfies the constraints.
virtual bool	isSatisfied (const Eigen::Ref< const Eigen::VectorXd > &x) const
	Check whether a state x satisfies the constraints.
unsigned int	getAmbientDimension () const
	Returns the dimension of the ambient space.
unsigned int	getManifoldDimension () const
	Returns the dimension of the manifold.
unsigned int	getCoDimension () const
	Returns the dimension of the manifold.
void	setManifoldDimension (unsigned int k)
	Sets the underlying manifold dimension.
double	getTolerance () const
	Returns the tolerance of the projection routine.
unsigned int	getMaxIterations () const
	Returns the maximum number of allowed iterations in the projection routine.
void	setTolerance (const double tolerance)
	Sets the projection tolerance.
void	setMaxIterations (const unsigned int iterations)
	Sets the maximum number of iterations in the projection routine.

Public Attributes
	links
	length
	width
	radius
	jointRadius
	obstacles
	extra
	walls
	cellSizes_

Static Public Attributes
	WALL_WIDTH
float	JOINT_RADIUS = 0.2
float	LINK_LENGTH = 1.0

Additional Inherited Members
Protected Attributes inherited from ompl::base::Constraint
const unsigned int	n_
	Ambient space dimension.
unsigned int	k_
	Manifold dimension.
double	tolerance_
	Tolerance for Newton method used in projection onto manifold.
unsigned int	maxIterations_
	Maximum number of iterations for Newton method used in projection onto manifold.

Detailed Description

Definition at line 54 of file ConstrainedPlanningImplicitChain.py.

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The documentation for this class was generated from the following file:

• ompl/demos/constraint/ConstrainedPlanningImplicitChain.py