让四足机器人像人一样快速躲闪动态障碍物
REBot: Reflexive Evasion Robot for Instantaneous Dynamic Obstacle Avoidance
- 用有限状态机整合避障与恢复策略，实现即时反应
- 仿真与实测中避障成功率显著提升，能耗更低
- 适合需要高速避障的机器人场景，如救援或竞赛
动态障碍物避让（DOA）对在有移动障碍物或人类环境中运行的四足机器人至关重要。现有方法通常依赖基于导航的轨迹重规划，假设具备充足反应时间，但在障碍物快速接近时易失效。此时，四足机器人需具备反射式避让能力，以实现即时、低延迟的机动。本文提出反射式避让机器人（REBot），一种控制框架，使四足机器人能实时实现反射式障碍物避让。REBot 在有限状态机中集成避障策略与恢复策略，通过精心设计的学习课程，并结合正则化与自适应奖励机制，在即时DOA任务中实现了鲁棒避让与快速稳定。我们通过大量仿真和真实实验验证了REBot，结果表明其在避障成功率、能量效率及对快速移动障碍物的鲁棒性方面均有显著提升。视频与附录见 https://rebot-2025.github.io/。
原文摘要 · Abstract (English)
Dynamic obstacle avoidance (DOA) is critical for quadrupedal robots operating in environments with moving obstacles or humans. Existing approaches typically rely on navigation-based trajectory replanning, which assumes sufficient reaction time and leading to fails when obstacles approach rapidly. In such scenarios, quadrupedal robots require reflexive evasion capabilities to perform instantaneous, low-latency maneuvers. This paper introduces Reflexive Evasion Robot (REBot), a control framework that enables quadrupedal robots to achieve real-time reflexive obstacle avoidance. REBot integrates an avoidance policy and a recovery policy within a finite-state machine. With carefully designed learning curricula and by incorporating regularization and adaptive rewards, REBot achieves robust evasion and rapid stabilization in instantaneous DOA tasks. We validate REBot through extensive simulations and real-world experiments, demonstrating notable improvements in avoidance success rates, energy efficiency, and robustness to fast-moving obstacles. Videos and appendix are available on https://rebot-2025.github.io/.
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