hpp-core  4.13.0
Implement basic classes for canonical path planning for kinematic chains.
Modules
Here is a list of all modules:
 Configuration SamplingRandom sampling of robot configurations for random path planning
 Path planning algorithmsPath planning algorithms derive from class hpp::core::PathPlanner
 Path OptimizationPath optimization algorithms derive from class hpp::core::PathOptimizer
 Steering method and distance functionsSome system are subject to kinematic or dynamic constraints. Those constraints can be handled in path planning using a steering method that builds an admissible path between two configurations of the system. When using a steering method, it can be useful to use a distance function that accounts for the cost to go from a configuration to another
 Validation of configurations and pathsPaths and configurations need to be validated with respect to various criteria (collision, joint bounds,...) during path planning and path optimization. Validation of a configuration or of a path gives rise to a validation report that provide information if validation failed
 RoadmapRandom sampling algorithm build a representation of the free configuration space as a graph called a roadmap. Nodes are configurations (or states) and edges are collision-free admissible paths (or trajectories)
 ConstraintsSome robots can be subject to constraints
 Path
 Plugins