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An Optimal Global Path Planning Algorithm for Mobile Robot Navigation

Anqi Guo, Gao Zheng, Renjing Gao

Year
2025
Citations
1

Abstract

ABSTRACT This paper proposes an optimal global path planning algorithm for wheeled mobile robot navigation based on the jump point search (JPS) algorithm, named Super JPS (S‐JPS). Firstly, a rigorous reformulation of jumping rules is proposed, and the concept of super jump points is introduced to address the problem of JPS lacking the ability to corner‐cutting moves. To further enhance the path‐finding speed, a novel method to determine the exploration direction by a bitwise operation is developed. Finally, a preprocessed grid map containing the direction and distance information of jump points is generated, and the jump points are identified a priori for path planning. Experimental results show that, without sacrificing optimality, the S‐JPS algorithm is significantly superior to the A* and JPS algorithms, which are suitable for mobile robot navigation in large‐scale environments.

Keywords

Motion planningMobile robotComputer scienceMobile robot navigationPath (computing)Artificial intelligenceComputer visionHuman–computer interactionRobotRobot control

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