Skip to content

A quasi Hybrid A* method is introduced for motion planning of autonomous driving car, based on MPC and Bezier spline

Notifications You must be signed in to change notification settings

xuedidi/Motion-planning-based-on-Model-Predictive-control-and-Bezier-spline

 
 

Repository files navigation

Motion-planning-based-on-Model-Predictive-control-and-Bezier-spline

A quasi Hybrid A* method is introduced for motion planning of autonomous driving car, based on MPC and Bezier spline

In this algorithm, the following factors are considered:

  1. Non-Holonomic feature of the vehicle
  2. Speed of the vehicle
  3. Start heading and steering angle
  4. Goal heading
  5. Grid size is 50mx50m

Non-Holonomic feature of the vehicle is taken into consideraion, so the path is continuous and drivable instead of discrete in the conventinoal A* algorithm.

Due to the usage of Bezier spline, no expand grid or heuristic layer is pre-computed as in Hybrid A*, making it very efficient.

The speed of vehicle is considered, thus it can minimize the error using model predictive control.

The pictures below show that the algorithm can plan a path according the starting/goal heading and steering. Also it can avoid obstacles and manage to return to Bezier spline as the reference path. The search tree (green dotted lines) is pruned due to the advantage of th Bezier spline.

Obstacle avoidance

Search tree

About

A quasi Hybrid A* method is introduced for motion planning of autonomous driving car, based on MPC and Bezier spline

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 84.8%
  • Python 15.2%