Decoupling Control for Heavy Quadruped Robot: A Hip-Based Optimal Virtual Force Distribution and Control Framework

Shaoxun Liu, Shiyu Zhou, Mohamed M. Abdullah, Zhengyu Pan, Jiliang Wang, Zhihua Niu, Rongrong Wang
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Abstract

The high self-weight and complex operating environment make implementing force sensor-based motion control of Heavy Quadruped Robots (HQR) challenging. In addition, for such robots, the mass of the heavy leg significantly impacts the ground reaction force (GRF) distribution and observation in the traditional control framework. This paper presents a GRF-Iess locomotion control framework for HQR based on five individual floating-base dynamics, fully considering the mass of legs and the coupled influence between the body and legs. We disassemble the full dynamics of the HQR into five spatially rigid parts with floating bases. The interaction effect between the body and legs is assumed to be a virtual spatial force (VSF), performing as the body's driving force and the loading force of the legs, which is obtained through the Nonlinear Disturbances Observer (NDOB). To realize the spatial trajectory control of the body, we utilize Quadratic Programming (QP) to solve the optimal VSF distribution on the body's hip joints. Furthermore, we employ Position-based Impedance Controllers (PIC) to build a VSF control loop to ensure that each grounded leg provides sufficient VSF to drive the body without slippage. Verification results show the promising locomotion control ability of the proposed framework for HQR.
重型四足机器人解耦控制:基于臀部的最优虚拟力分配与控制框架
重型四足机器人的高自重和复杂的操作环境给基于力传感器的运动控制带来了挑战。此外,对于这类机器人,在传统的控制框架中,重型腿的质量对地面反作用力(GRF)的分布和观测有很大的影响。本文提出了一种基于5个独立浮基动力学的机器人无grf运动控制框架,充分考虑了腿的质量以及身体与腿之间的耦合影响。我们将HQR的完整动力学分解为五个具有浮动基座的空间刚性部分。通过非线性扰动观测器(NDOB)获取机器人的身体和腿之间的相互作用力,并将其假设为一种虚拟空间力(VSF),作为机器人身体的驱动力和腿的加载力。为了实现人体的空间轨迹控制,我们利用二次规划(QP)求解人体髋关节上的最优VSF分布。此外,我们采用基于位置的阻抗控制器(PIC)来构建VSF控制回路,以确保每个接地腿提供足够的VSF来驱动身体而不会打滑。验证结果表明,该框架具有良好的运动控制能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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