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作 者:杜国锋 赵萌 武建昫 张东 DU Guofeng;ZHAO Meng;WU Jianxu;ZHANG Dong(College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029;School of Mechanical,Electronic and Control Engineering,Beijing Jiaotong University,Beijing 100044)
机构地区:[1]北京化工大学信息科学与技术学院,北京100029 [2]北京交通大学机械与电子控制工程学院,北京100044
出 处:《机械工程学报》2024年第19期62-70,共9页Journal of Mechanical Engineering
基 金:北京市自然科学基金小米联合基金(L223019);北京市自然科学基金(3242011)资助项目。
摘 要:闭链多足机器人环境适应性强、稳定性高,具备复杂户外环境下运动的潜力,然而现有基于模型的控制方法难以主动获取地形信息,在复杂户外环境中自主行走难度大;基于视觉的方法能够主动获取环境信息,但难以根据地形自主切换步态。为此,提出了基于视觉的闭链多足机器人自主运动控制方法,建立了从视觉图像到步态的直接映射。主要内容包括:通过运动学分析和数据拟合建立运动学模型和越障策略;采用融合YOLACT++的地形可通行域划分算法,基于中点像素采样法在可通域内生成导航路径。为验证所提方法,搭建了多地形组合仿真场景和实际场景并进行实验,结果表明闭链多足机器人能够在陌生环境下自主行走,且能够根据地形切换步态。Closed-chain multi-legged robots have strong environmental adaptability and high stability.They have the potential to move in complex outdoor environments.However,existing model-based control methods are difficult to use in actively obtaining terrain information and to walk autonomously in complex outdoor scenarios.Vision-based methods are able to acquire environmental information actively,but the robot has difficult in switching gaits autonomously according to the terrain.With regards to this,a vision-based closed-chain autonomous motion control method for multi-legged robots is proposed,and a mapping from visual images to gaits is established.The kinematic model and obstacle-crossing strategy are established through kinematic analysis and data fitting.The terrain passable domain delineation algorithm incorporating YOLACT++is used to generate navigation paths in the passable domain based on the midpoint pixel sampling method.In order to validate the proposed method,a multi-terrain simulation scene and a real scene are built and experimented,and the results show that the closed-chained multi-legged robot is able to walk autonomously in unfamiliar environments and switch its gaits according to the terrain.
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
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