Global path planning method based on potential energy guided rapid search random tree algorithm

By generating a potential energy map and incorporating it into the RRT* algorithm, safe path points are selected, solving the problem of traditional RRT* algorithm trajectories closely following obstacles and achieving safer path planning.

CN121612335BActive Publication Date: 2026-05-08JILIN UNIVERSITY
2 Cites 0 Cited by

Patent Information

Application Number
CN202610148759.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-02-03
Publication Date
2026-05-08
Estimated Expiration
2046-02-03

AI Technical Summary

Technical Problem

Traditional fast random tree search (RRT* algorithm) algorithms typically only consider that obstacles will block node connections, resulting in the planned trajectory closely following the obstacles, which does not reflect the actual driving situation.

Method used

By calculating the potential energy value of obstacles relative to any point, a potential energy map matrix is ​​generated and introduced into the RRT* algorithm. A potential energy threshold is set to filter randomly generated points, and the potential energy value is incorporated into the cost function to optimize path planning and ensure path safety and reasonable distance.

Benefits of technology

The generated path remains within a safe zone, giving drivers enough time to respond to emergencies, improving driving safety, and meeting actual driving needs.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The global path planning method based on potential energy guidance fast search random tree algorithm belongs to the technical field of intelligent vehicle path planning, and solves the technical problem that the traditional fast search random tree algorithm can cause the planned trajectory to travel close to the obstacles. First, the position of the obstacles and the start and end positions are determined through the two-dimensional space map planned by the vehicle. For any point in the map, the potential energy value thereof is calculated, and the potential energy values of all the obstacles are superimposed to obtain the potential energy value of the arbitrary point. The potential energy values of all the arbitrary points in the two-dimensional space map are obtained in the same way. Then, the potential energy values of each point of the whole map are normalized to obtain a potential energy map matrix. The potential energy map matrix is introduced into the fast search random tree algorithm, a potential energy threshold is set, and the randomly generated points are screened. After screening, the potential energy values are introduced into the cost function of the fast search random tree algorithm, and rewiring optimization is performed, so as to perform vehicle path planning.
Need to check novelty before this filing date? Find Prior Art