Whole-body control (WBC) is a generic task-oriented control method for feedback control of loco-manipulation behaviors in humanoid robots. The combination of WBC and model-based walking controllers has been widely utilized in various humanoid robots. However, to date, the WBC method has not been employed for unsupported passive-ankle dynamic locomotion. As such, in this article, we devise a new WBC, dubbed the whole-body locomotion controller (WBLC), that can achieve experimental dynamic walking on unsupported passive-ankle biped robots. A key aspect of WBLC is the relaxation of contact constraints such that the control commands produce reduced jerk when switching foot contacts. To achieve robust dynamic locomotion, we conduct an in-depth analysis of uncertainty for our dynamic walking algorithm called the time-to-velocity-reversal (TVR) planner. The uncertainty study is fundamental as it allows us to improve the control algorithms and mechanical structure of our robot to fulfill the tolerated uncertainty. In addition, we conduct extensive experimentation for: (1) unsupported dynamic balancing (i.e., in-place stepping) with a six-degree-of-freedom biped, Mercury; (2) unsupported directional walking with Mercury; (3) walking over an irregular and slippery terrain with Mercury; and 4) in-place walking with our newly designed ten-DoF viscoelastic liquid-cooled biped, DRACO. Overall, the main contributions of this work are on: (a) achieving various modalities of unsupported dynamic locomotion of passive-ankle bipeds using a WBLC controller and a TVR planner; (b) conducting an uncertainty analysis to improve the mechanical structure and the controllers of Mercury; and (c) devising a whole-body control strategy that reduces movement jerk during walking.

中文翻译：

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使用全身运动控制的被动踝双足机器人和类人动物的动态运动

全身控制 (WBC) 是一种通用的面向任务的控制方法，用于对仿人机器人的位置操纵行为进行反馈控制。WBC 与基于模型的步行控制器的结合已广泛应用于各种仿人机器人。然而，迄今为止，WBC 方法尚未用于无支撑的被动踝关节动态运动。因此，在本文中，我们设计了一种新的 WBC，称为全身运动控制器 (WBLC)，它可以在无支撑的被动脚踝双足机器人上实现实验性动态行走。WBLC 的一个关键方面是放松接触约束，以便控制命令在切换脚接触时产生减少的冲击。为了实现稳健的动态运动，我们对称为时间速度反转 (TVR) 规划器的动态步行算法的不确定性进行了深入分析。不确定性研究是基础，因为它允许我们改进机器人的控制算法和机械结构，以满足可容忍的不确定性。此外，我们还针对以下内容进行了广泛的实验：(1) 使用六自由度 Biped Mercury 进行无支撑动态平衡（即原位步进）；(2) 与水星无支撑定向行走；(3) 与水星一起走过不规则和湿滑的地形；4) 使用我们新设计的 10 自由度粘弹性液冷双足动物 DRACO 进行原地行走。总体而言，这项工作的主要贡献在于：(a) 使用 WBLC 控制器和 TVR 规划器实现被动踝双足动物无支撑动态运动的各种模式；(b) 进行不确定性分析以改进水星的机械结构和控制器；