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Realizing underactuated bipedal walking with torque controllers via the ideal model resolved motion method

机译:通过理想的模型解析运动方法,利用扭矩控制器实现欠驱动的双足行走

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This paper presents experimentally realized bipedal robotic walking using ideal torque controllers via a novel approach termed the ideal model resolved motion method (IM-RMM), where a system's ideal closed-loop dynamics are integrated forward from the actual state of the hardware to provide desired positions and velocity commands to a PD controller. By combining this method with gaits generated using the Human-Inspired Control framework, walking was realized experimentally on the DURUS platform, designed and built by SRI, and achieved with minimal system identification. For comparison, two controllers, one using feedback linearization and one using Control Lyapunov Function based Quadratic Programs (CLF-QP), both realized through IM-RMM, are compared with a benchmark procedure, the Hybrid Zero Dynamics reconstruction, that is shown to provide reliable walking in literature. The results of both simulations and experiments are presented, with the CLF-QP implemented via IM-RMM resulting in the lowest experimental specific energetic cost of transport of c = 0.63 achieved during sustained walking on the 31.5 kg bipedal robot.
机译:本文介绍了一种通过理想扭矩控制器通过实验实现的双足机器人行走,这种新颖的方法被称为理想模型解析运动方法(IM-RMM),该方法从硬件的实际状态向前集成了系统的理想闭环动态特性,以提供所需的期望值。 PD控制器的位置和速度命令。通过将该方法与使用Human-Inspired Control框架生成的步态相结合,可以在由SRI设计和构建的DURUS平台上通过实验实现步行,并且只需最少的系统识别即可实现。为了进行比较,将两个均通过IM-RMM实现的控制器(其中一个使用反馈线性化,一个使用基于控制Lyapunov函数的二次程序(CLF-QP))与基准程序(混合零动态重构)进行比较,该程序可提供可靠的文学作品。给出了仿真和实验的结果,并通过IM-RMM实施了CLF-QP,从而在31.5 kg的双足机器人持续行走过程中实现了最低的实验单位能量特定运输成本c = 0.63。

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