模型预测控制
控制理论(社会学)
稳健性(进化)
脉冲(物理)
计算机科学
机器人
控制器(灌溉)
扭矩
模拟
控制工程
工程类
控制(管理)
人工智能
物理
基因
热力学
生物
量子力学
化学
生物化学
农学
作者
D. Kim,Jared Di Carlo,Benjamin Katz,Gerardo Bledt,Sangbae Kim
出处
期刊:Cornell University - arXiv
日期:2019-09-14
被引量:25
摘要
Dynamic legged locomotion is a challenging topic because of the lack of established control schemes which can handle aerial phases, short stance times, and high-speed leg swings. In this paper, we propose a controller combining whole-body control (WBC) and model predictive control (MPC). In our framework, MPC finds an optimal reaction force profile over a longer time horizon with a simple model, and WBC computes joint torque, position, and velocity commands based on the reaction forces computed from MPC. Unlike existing WBCs, which attempt to track commanded body trajectories, our controller is focused more on the reaction force command, which allows it to accomplish high speed dynamic locomotion with aerial phases. The newly devised WBC is integrated with MPC and tested on the Mini-Cheetah quadruped robot. To demonstrate the robustness and versatility, the controller is tested on six different gaits in a number of different environments, including outdoors and on a treadmill, reaching a top speed of 3.7 m/s.
科研通智能强力驱动
Strongly Powered by AbleSci AI