Modeling and controlling legged robot locomotion on terrains with densely distributed large rocks and boulders are fundamentally challenging. Unlike traditional methods, which often consider these rocks and boulders as obstacles and attempt to find a clear path to circumvent them, in this study, we aim to develop methods for robots to actively utilize interaction forces with these “obstacles” for locomotion and navigation. To do so, we studied the locomotion of a quadrupedal robot as it traversed a simplified obstacle field with 12 different gaits and discovered that with each gait, the robot could passively converge to a distinct orientation. A compositional return map explained this observed passive convergence and enabled prediction of the steady-state orientation angles for each quadrupedal gait. We experimentally demonstrated that with these predictions, a legged robot could effectively generate the desired shape of trajectories among large, slippery obstacles, simply by switching between different gaits. Our study offered a novel method for robots to exploit traditionally-considered “obstacles” to achieve agile movements on challenging terrains.

中文翻译：

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通过顺序步态组合进行四足机器人的障碍辅助轨迹控制


在具有密集分布的大岩石和巨石的地形上建模和控制腿式机器人的运动具有根本性的挑战性。传统方法通常将这些岩石和巨石视为障碍，并试图找到一条清晰的路径来绕过它们，而在这项研究中，我们的目标是开发一种方法，让机器人主动利用与这些“障碍”的相互作用力来进行运动和导航。为此，我们研究了四足机器人以 12 种不同步态穿越简化的障碍物时的运动，并发现在每种步态中，机器人都可以被动地收敛到不同的方向。组合返回图解释了这种观察到的被动收敛，并能够预测每个四足步态的稳态方向角。我们通过实验证明，通过这些预测，足式机器人只需在不同的步态之间切换，就可以在大型、湿滑的障碍物中有效地生成所需的轨迹形状。我们的研究为机器人提供了一种新颖的方法，可以利用传统上认为的“障碍”来实现在具有挑战性的地形上的敏捷运动。