让四足机器人像动物一样敏捷穿越狭窄门洞。
Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
- 分层强化学习：低层模仿动物行为生成多样技能，高层基于视觉决策路径。
- 实现无需预设轨迹的自主空中穿越窄门，避免碰撞且动作剧烈。
- 框架可扩展至其他高动态任务，适合研究仿生机器人运动控制者。
尽管腿式动物能在狭小空间中完成爆发性运动，但将此类行为复现于四足机器人仍是一大挑战。本文提出一种分层强化学习流程，使机器人能够通过狭窄门洞执行激进运动。低层策略通过模仿学习模拟真实动物行为，生成多样化技能；高层控制器结合底层技能能力与视觉感知的门洞信息，规划无碰撞的动态穿越轨迹。值得注意的是，该框架还可推广至其他高动态任务。这是首个在地面行走机器人上实现自主、敏捷空中穿越门洞的工作，显著提升了四足机器人运动的类生物灵巧性。
原文摘要 · Abstract (English)
Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots has been a longstanding challenge. Here, we propose a hierarchical reinforcement learning pipeline that empowers the robots to perform aggressive locomotion through constrained obstacles--a narrow gate. The imitation learning technique is used to train the low-level policy, which mimics the behaviors of real animals and forms a set of diverse skills. The high-level controller, having an awareness of the capability of low-level skills and acquiring the gate information via vision-based detection, determines the suitable maneuvers with collision-free trajectories to traverse it dynamically. Notably, we also verify that this framework can be extended to other highly dynamic tasks. This is one of the first works that perform autonomous and agile aerial gate traversal tasks on ground-walking robots, extending the lifelike agility of legged robots to match that of their biological counterparts.
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