提出实时验证足点可达性的新方法，提升机器人在复杂环境中的运动能力。
KCFRC: Kinematic Collision-Aware Foothold Reachability Criteria for Legged Locomotion
- 基于运动学建立足点可达性充分条件，实现快速验证。
- 单腿900个候选足点平均仅需2毫秒完成检查。
- 适用于狭小空间的接触规划，显著提升机器人适应性。
足式机器人在复杂环境中导航面临巨大挑战，需实时精准决策足点选择与接触规划。尽管已有研究基于地形几何或运动学选取足点，但极少方法能高效验证非碰撞摆动轨迹的存在性。本文提出KCFRC方法，首次形式化定义足点可达性问题，并建立其充分条件。基于此，设计出可实时验证足点可达性的算法。实验表明，该方法对单腿900个潜在足点的可达性检查平均耗时仅2毫秒。同时，KCFRC可加速轨迹优化，在受限空间中显著增强接触规划能力，提升足式机器人在复杂环境下的适应性与鲁棒性。
原文摘要 · Abstract (English)
Legged robots face significant challenges in navigating complex environments, as they require precise real-time decisions for foothold selection and contact planning. While existing research has explored methods to select footholds based on terrain geometry or kinematics, a critical gap remains: few existing methods efficiently validate the existence of a non-collision swing trajectory. This paper addresses this gap by introducing KCFRC, a novel approach for efficient foothold reachability analysis. We first formally define the foothold reachability problem and establish a sufficient condition for foothold reachability. Based on this condition, we develop the KCFRC algorithm, which enables robots to validate foothold reachability in real time. Our experimental results demonstrate that KCFRC achieves remarkable time efficiency, completing foothold reachability checks for a single leg across 900 potential footholds in an average of 2 ms. Furthermore, we show that KCFRC can accelerate trajectory optimization and is particularly beneficial for contact planning in confined spaces, enhancing the adaptability and robustness of legged robots in challenging environments.
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