ConstrainedPlanningTorus.TorusConstraint Class Reference
Inheritance diagram for ConstrainedPlanningTorus.TorusConstraint:

Public Member Functions

def __init__ (self, outer, inner, maze)
 
def getStartAndGoalStates (self)
 
def function (self, x, out)
 
def jacobian (self, x, out)
 
def ambientToMaze (self, x)
 
def mazeToAmbient (self, x)
 
def mazePixel (self, x)
 
def isValid (self, state)
 
- 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.
 
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.
 
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.
 
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.
 
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.
 
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

 outer
 
 inner
 
 ppm
 

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 51 of file ConstrainedPlanningTorus.py.


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