An improved path planning and tracking control method for planetary exploration rovers with traversable tolerance

Abstract

In order to ensure the safety and efficiency of planetary exploration rovers, path planning and tracking control of a planetary rover are expected to consider factors such as complex 3D terrain features, the motion constraints of the rover, traversability, etc. An improved path planning and tracking control method is proposed for planetary exploration rovers on rough terrain in this paper. Firstly, the kinematic model of the planetary rover is established. A 3D motion primitives library adapted to various terrains and the rover’s orientations is generated. The state expansion process and heuristic function of the A* algorithm are improved using the motion primitives and terrain features. Global path is generated by improved A*-based algorithm that satisfies the planetary rover’s kinematic constraints and the 3D terrain restrictions. Subsequently, an optional arc path set is designed based on the traversable capabilities of the planetary rover. Each arc path corresponds to a specific motion that determines the linear and angular velocities of the planetary rover. The optimal path is selected through the multi-objective evaluation function. The planetary rover is driven to accurately track the global path by sending optimal commands that corresponds to the optimal path for real-time obstacle avoidance. Finally, the path planning and tracking control method is effectively validated during a given mission through two simulation tests. The experiment results show that the improved A*-based algorithm reduces planning time by 30.05% and generates smoother paths than the classic A* algorithm. The multi-objective arc-based method improves the rover’s motion efficiency, ensuring safer and quicker mission completion along the global path.

Keywords

Planetary exploration rovers / Path planning / Motion primitives / Optional arc paths

CRediT authorship contribution statement

Haojie Zhang: Writing - review & editing, Conceptualization. Feng Jiang: Writing - original draft, Methodology. Qing Li: Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was funded by the State Key Laboratory, China (KJW6142210210308) and the National Natural Science Foundation of China (61806183).

Appendix A. Supplementary data

Supplementary material related to this article can be found online at https://doi.org/10.1016/j.birob.2025.100219.

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