Python codes for robotics Trajectory-Planning-Hybrid-A-Star algorithm.

This is a Hybrid-A-Star-Trajectory-Planner.
This method can do the Trajectory-Planning based on Multi-Vehicle-Movement-Sequence-Planning.
The trajectory can be used for non-holonomic vehicle.

We have obtained the planning results based on the topological map.
Now we want to do trajectory planning based on grid-based map.

Hybrid A* Planner
Graph：State Lattice + Grid Map
Trajectory：Reeds Shepp Path Generator（non-holonomic）
Algorithm：Based on A*
Input：1. Start state；2. Goal state；3. Grid-based Map； Output：Trajectory

State Lattice uses the model predictive trajectory generator to solve boundary problem.

Ref:
Optimal rough terrain trajectory generation for wheeled mobile robots State Space Sampling of Feasible Motions for High-Performance Mobile Robot Navigation in Complex Environments

Ref:
Practical Search Techniques in Path Planning for Autonomous Driving