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. | |
| 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 | |
| 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:
- ompl/demos/constraint/ConstrainedPlanningTorus.py