Capsizing-Guided Trajectory Optimization for Autonomous Navigation with Rough Terrain

TL;DR

This paper introduces a capsizing-aware trajectory planner for ground robots navigating rough terrain, ensuring safety against tip-over while optimizing for effective navigation in challenging environments.

Contribution

The paper presents a novel capsizing-aware trajectory planning method that incorporates stability constraints into the optimization process for safer navigation on uneven terrain.

Findings

The proposed method improves navigation safety and robustness.

CAP outperforms existing approaches in simulations and real-world tests.

The approach effectively prevents robot tip-over in complex terrains.

Abstract

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.