Entanglements like vines and branches in natural settings or cords and pipes in human spaces prevent mobile robots from accessing many environments. Legged robots should be effective in these settings, and more so than wheeled or tracked platforms, but naive controllers quickly become entangled and stuck. In this paper we present a method for proprioception aimed specifically at the task of sensing entanglements of a robot's legs as well as a reaction strategy to disentangle legs during their swing phase as they advance to their next foothold. We demonstrate our proprioception and reaction strategy enables traversal of entanglements of many stiffnesses and geometries succeeding in 14 out of 16 trials in laboratory tests, as well as a natural outdoor environment.

翻译：自然环境中藤蔓和树枝、或人类空间中电线和管道等纠缠物，阻碍了移动机器人进入许多环境。腿足机器人在这些场景中本应比轮式或履带式平台更有效，但简单的控制器会迅速被纠缠并卡住。本文提出了一种专门用于感知机器人腿部纠缠的本体感知方法，以及一种在摆动阶段使腿部脱离纠缠并前进至下一个立足点的反应策略。实验表明，我们的本体感知与反应策略使机器人能够穿越多种刚度和几何形状的纠缠物，在实验室测试的16次试验中成功14次，并在自然户外环境中同样表现良好。