ScholarWorks@성균관대학교

초록

Quadruped robots exhibit superior terrain adaptability and mobility, enabling autonomous navigation in complex environments. However, path planning for quadruped robots is inherently challenging due to the non-circular and high-dimensional nature of their collision model, which introduces a trade-off between collision detection accuracy and planning robustness. To overcome this challenge, we propose the concept of a 3D Rotatable Area (3D RoA). The 3D RoA represents the range of collision-free and stable yaw angles at a given position, explicitly capturing local terrain geometry and collision constraints. Based on the 3D RoA, we further present a path planning framework that efficiently recognizes and navigates highly cluttered environments. Our approach generates traversable and collision-free SE(3) paths through 2D search, reducing the search space while accurately handling the collision geometry of the quadruped robot.

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