Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failure, especially in real-world environments with unexpected height variations such as rocky hills or curbs. To enable dynamic traversal of extreme terrain, this work introduces 1) a proprioception-based gait planner for estimating unknown hybrid events due to elevation changes and responding by modifying contact schedules and planned footholds online, and 2) a two-degree-of-freedom tail for improving contact-independent control and a corresponding decoupled control scheme for better versatility and efficiency. Simulation results show that the gait planner significantly improves stability under unforeseen terrain height changes compared to methods that assume fixed contact schedules and footholds. Further, tests have shown that the tail is particularly effective at maintaining stability when encountering a terrain change with an initial angular disturbance. The results show that these approaches work synergistically to stabilize locomotion with elevation changes up to 1.5 times the leg length and tilted initial states.

翻译：足式机器人通过地面接触及其反作用力实现敏捷运动。然而，接触不连续性与不确定性会导致失效，尤其在存在意外高度变化的真实环境（如岩石丘陵或路缘）中。为实现在极端地形中的动态穿越，本工作提出：1）基于本体感觉的步态规划器，用于估计地形高度变化导致的未知混合事件，并通过在线调整接触时序与规划足端落点进行响应；2）双自由度尾部结构以提升非接触式控制能力，并配套解耦控制策略以增强通用性与效率。仿真结果表明，与假设固定接触时序与足端落点的方法相比，该步态规划器在非预期地形高度变化下显著提升稳定性。此外，测试显示尾部在遭遇带有初始角扰动的地形变化时，对维持稳定性尤为有效。结果表明，这些方法协同作用，可在腿长1.5倍的高度变化及倾斜初始状态下实现稳定运动。