ORIGINAL RESEARCH article

Front. Neurorobot.

Volume 19 - 2025 | doi: 10.3389/fnbot.2025.1605938

Hexapod Robot Motion Planning Investigation Under the Influence of Multi-dimensional Terrain Features

Provisionally accepted
Chen  ChenChen ChenJunbo  LinJunbo LinBo  YouBo You*Jiayu  LiJiayu LiBiao  GaoBiao Gao
  • Harbin University of Science and Technology, Harbin, China

The final, formatted version of the article will be published soon.

To address the challenges arising from the coupled interactions between multi-dimensional terrain features-encompassing both geometric and physical properties of complex field environments-and the locomotion stability of hexapod robots, this paper presents a comprehensive motion planning framework incorporating multi-dimensional terrain information. The proposed methodology systematically extracts multi-dimensional geometric and physical terrain features from a multi-layered environmental map. Based on these features, a traversal cost map is synthesized, and an enhanced A* algorithm is developed that incorporates terrain traversal metrics to optimize path planning safety across complex field environments. Furthermore, the framework introduces a foothold cost map derived from multi-dimensional terrain data, coupled with a fault-tolerant free gait planning algorithm based on foothold cost evaluation. This approach enables dynamic gait modulation to enhance overall locomotion stability while maintaining safe trajectory planning. The efficacy of the proposed framework is validated through both simulation studies and physical experiments on a hexapod robotic platform. Experimental results demonstrate that, compared to conventional hexapod motion planning approaches, the proposed multi-dimensional terrain-aware planning framework significantly enhances both locomotion safety and stability across complex field environments.

Keywords: Hexapod robot, Locomotion stability, multi-dimensional terrain features, path planning, free gait planning

Received: 04 Apr 2025; Accepted: 01 May 2025.

Copyright: © 2025 Chen, Lin, You, Li and Gao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Bo You, Harbin University of Science and Technology, Harbin, China

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