四足机器人在复杂地形下的全身运动规划与控制

IF 4.2 2区 计算机科学 Q2 ROBOTICS Journal of Field Robotics Pub Date : 2023-05-23 DOI:10.1002/rob.22197
Guanglin Lu, Teng Chen, Xuewen Rong, Guoteng Zhang, Jian Bi, Jingxuan Cao, Han Jiang, Yibin Li
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引用次数: 0

摘要

在丛林、山区或工厂工作的四足机器人应该能够在具有挑战性的场景中移动。在本文中,我们提出了一个四足机器人在崎岖地形上行走的控制框架。利用归一化能量稳定准则对机器人的重心轨迹进行规划,保证机器人处于最稳定状态。提出了一种基于概率接触模型的接触检测算法,实现了四足机器人腿部基于事件的状态切换。提出了一种基于广义动量的接触力在线检测方法,提高了本体感觉力估计的准确性。提出了一种结合全身控制和虚拟模型控制的控制器,以实现精确的轨迹跟踪和对环境交互的主动顺应。在不了解环境的情况下,设计了四足机器人SDUQuad-144爬过38 cm高的台阶和22.5 cm高的楼梯等重大障碍物的实验,验证了所提出方法的可行性。
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Whole-body motion planning and control of a quadruped robot for challenging terrain

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.

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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
期刊最新文献
Issue Information Cover Image, Volume 41, Number 8, December 2024 Issue Information Issue Information A CIELAB fusion-based generative adversarial network for reliable sand–dust removal in open-pit mines
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