Metastable Walking on Stochastically Rough Terrain
Metastable Walking on Stochastically Rough Terrain
复制标题
随机崎岖地形上的亚稳态行走
DOI：
--
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Russ Tedrake
中科院分区：
文献类型：
--
作者：
Katie Byl;Russ Tedrake
在平坦地形上的极限环行走的简化模型提供了重要的见解，腿的运动的性质。然而，真正的行走机器人（和人类）并没有表现出真正的极限环动力学，因为即使在精心设计的实验室环境中，地形也不可避免地是非平坦的。随机崎岖地形上的行走系统可能不满足严格的极限环稳定性条件，但仍然可以表现出令人印象深刻的长寿命连续行走周期。在这里，我们研究了无轮和罗经步态在随机生成的粗糙地形上行走的动力学，并使用随机过程的工具来描述这些步态的“随机稳定性”。该分析推广了我们对步行稳定性的理解，并可为实际步行系统的极限环实验分析提供统计工具。
Simplified models of limit-cycle walking on flat terrain have provided important insights into the nature of legged locomotion. Real walking robots (and humans), however, do not exhibit true limit cycle dynamics because terrain, even in a carefully designed laboratory setting, is inevitably non-flat. Walking systems on stochastically rough terrain may not satisfy strict conditions for limit-cycle stability but can still demonstrate impressively long-living periods of continuous walking. Here, we examine the dynamics of rimless-wheel and compass-gait walking on randomly generated rough terrain and employ tools from stochastic processes to describe the ‘stochastic stability’ of these gaits. This analysis generalizes our understanding of walking stability and may provide statistical tools for experimental limit cycle analysis on real walking systems.