Analysis and control techniques for the compass gait with a torso walking on stochastically rough terrain
Analysis and control techniques for the compass gait with a torso walking on stochastically rough terrain
复制标题
随机崎岖地形躯干行走罗盘步态分析与控制技术
DOI：
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Katie Byl
中科院分区：
文献类型：
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作者：
Min;Katie Byl
利用倒立摆动力学的动态步行步态已被证明是机器人运动的重要保证。例如，这些步态可以减少能量消耗以及水平地面行走所需的致动器的数量和复杂性。然而，采用动态步态的机器人步行者通常对地形变化也非常敏感。在本文中，我们专注于开发改进的控制策略，并分析所产生的稳定性的一个简单而有效的模型，在崎岖的地形上行走的新方法。我们的主要贡献如下。(1)我们量化的稳定值添加躯干的标准指南针步态模型;（2）我们优化了一类简单的控制器在这个步行者是强大的未感知到的变化，即将到来的地形高度;（3）我们开发了改进的数值工具，用于估计跌倒事件的统计粗糙地形行走。我们的研究结果表明，躯干步行者可以处理约14%的腿长的地形意外的步骤变化，我们的统计工具是有效的6维状态空间系统，表明承诺在挑战中解决维数灾难时，应用机器学习技术，粗糙地形行走。
Dynamic walking gaits which exploit inverted pendulum dynamics have demonstrated significant promise for biped robot locomotion. For example, these gaits can reduce the energy expended and the number and complexity of actuators required for level-ground walking. However, robot walkers employing dynamic gaits are, in general, also notoriously sensitive to terrain variations. In this paper, we focus on new methods for developing improved control strategies for and analyzing resulting stability of a simple yet effective model for biped walking on rough terrain. Our primary contributions are as follows. (1) We quantify the stabilizing value of adding a torso to the standard compass gait model; (2) we optimize a class of simple controllers on this walker to be robust to unsensed changes in upcoming terrain height; and (3) we develop improved numerical tools for estimating the statistics of fall events for rough terrain walking. Our results indicate that the torso walker can handle unanticipated step changes in terrain of approximately 14% of leg length, and that our statistical tools are effective for a 6-dimensional state space system, indicating promise in the challenge of addressing the curse of dimensionality when applying machine learning techniques to rough terrain walking.
DOI：
10.1115/1.1427703
发表时间：
2002-02-01
影响因子：
1.7
作者：
Kuo, AD
通讯作者：
Kuo, AD