ConstrainedPlanningSphere.SphereConstraint Class Reference

Inheritance diagram for ConstrainedPlanningSphere.SphereConstraint:

## Public Member Functions | |

def | __init__ (self) |

def | function (self, x, out) |

def | jacobian (self, x, out) |

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. | |

## 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 46 of file ConstrainedPlanningSphere.py.

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

- ompl/demos/constraint/ConstrainedPlanningSphere.py