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