机器人
控制理论(社会学)
弹道
地形
控制器(灌溉)
模拟
跟踪(教育)
计算机科学
工程类
概率逻辑
控制工程
控制(管理)
人工智能
地理
心理学
教育学
物理
天文
农学
生物
地图学
作者
Guanglin Lu,Teng Chen,Xuewen Rong,Guoteng Zhang,Jian Bi,Jingxuan Cao,Han Jiang,Yibin Li
摘要
Abstract Quadruped robots working in jungles, mountains or factories should be able to move through challenging scenarios. In this paper, we present a control framework for quadruped robots walking over rough terrain. The planner plans the trajectory of the robot's center of gravity by using the normalized energy stability criterion, which ensures that the robot is in the most stable state. A contact detection algorithm based on the probabilistic contact model is presented, which implements event‐based state switching of the quadruped robot legs. And an on‐line detection of contact force based on generalized momentum is also showed, which improves the accuracy of proprioceptive force estimation. A controller combining whole body control and virtual model control is proposed to achieve precise trajectory tracking and active compliance with environment interaction. Without any knowledge of the environment, the experiments of the quadruped robot SDUQuad‐144 climbs over significant obstacles such as 38 cm high steps and 22.5 cm high stairs are designed to verify the feasibility of the proposed method.
科研通智能强力驱动
Strongly Powered by AbleSci AI