Capsizing-Guided Trajectory Optimization for Autonomous Navigation with Rough Terrain
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913984771260416 |
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| author | Zhang, Wei Wang, Yinchuan Lu, Wangtao Zhang, Pengyu Zhang, Xiang Wang, Yue Wang, Chaoqun |
| author_facet | Zhang, Wei Wang, Yinchuan Lu, Wangtao Zhang, Pengyu Zhang, Xiang Wang, Yue Wang, Chaoqun |
| contents | It is a challenging task for ground robots to autonomously navigate in harsh environments due to the presence of non-trivial obstacles and uneven terrain. This requires trajectory planning that balances safety and efficiency. The primary challenge is to generate a feasible trajectory that prevents robot from tip-over while ensuring effective navigation. In this paper, we propose a capsizing-aware trajectory planner (CAP) to achieve trajectory planning on the uneven terrain. The tip-over stability of the robot on rough terrain is analyzed. Based on the tip-over stability, we define the traversable orientation, which indicates the safe range of robot orientations. This orientation is then incorporated into a capsizing-safety constraint for trajectory optimization. We employ a graph-based solver to compute a robust and feasible trajectory while adhering to the capsizing-safety constraint. Extensive simulation and real-world experiments validate the effectiveness and robustness of the proposed method. The results demonstrate that CAP outperforms existing state-of-the-art approaches, providing enhanced navigation performance on uneven terrains. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_08108 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Capsizing-Guided Trajectory Optimization for Autonomous Navigation with Rough Terrain Zhang, Wei Wang, Yinchuan Lu, Wangtao Zhang, Pengyu Zhang, Xiang Wang, Yue Wang, Chaoqun Robotics It is a challenging task for ground robots to autonomously navigate in harsh environments due to the presence of non-trivial obstacles and uneven terrain. This requires trajectory planning that balances safety and efficiency. The primary challenge is to generate a feasible trajectory that prevents robot from tip-over while ensuring effective navigation. In this paper, we propose a capsizing-aware trajectory planner (CAP) to achieve trajectory planning on the uneven terrain. The tip-over stability of the robot on rough terrain is analyzed. Based on the tip-over stability, we define the traversable orientation, which indicates the safe range of robot orientations. This orientation is then incorporated into a capsizing-safety constraint for trajectory optimization. We employ a graph-based solver to compute a robust and feasible trajectory while adhering to the capsizing-safety constraint. Extensive simulation and real-world experiments validate the effectiveness and robustness of the proposed method. The results demonstrate that CAP outperforms existing state-of-the-art approaches, providing enhanced navigation performance on uneven terrains. |
| title | Capsizing-Guided Trajectory Optimization for Autonomous Navigation with Rough Terrain |
| topic | Robotics |
| url | https://arxiv.org/abs/2508.08108 |