首页|Vision-based docking system for an aromatic-hydrocarbon-inspired reconfigurable robot

Vision-based docking system for an aromatic-hydrocarbon-inspired reconfigurable robot

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Aromatic hydrocarbons generally refer to compounds containing benzene rings.Many types of isomers can be formed by replac-ing hydrogen atoms on the benzene ring.In this paper,an aromatic-hydrocarbon-inspired modular robot(AHIMR)is proposed.The robot can be reassembled into different configurations suitable for various task requirements.A vision-based docking system is designed for the AHIMR.The system primarily consists of two stages:a remote guidance stage and a precise docking stage.During the remote guidance stage,an object module is identified using an illumination adaptive target recognition algorithm,and then the active module moves to the docking area through communication with ZigBee.In the precise docking stage,the active module calculates the relative pose with the object module using a perspective-n-point method and dynamically adjusts its posture to dock.In this process,a Kalman filter is used to reduce target occlusion and jitter interference.In addition,the docking system feasibility is verified via several simulation experiments.The module docking accuracy is controlled within 0.01 m,which meets the reconfiguration task requirements of the AHIMR.In the AHIMR submodule docking experiment,the active module accurately moves to the expected position with a docking success rate of 95%.

modular robot reconfigurationaromatic hydrocarbonautonomous dockingvisual identification

XING FangYi、XU Cheng、LIU JinGuo、XUE ZhiHui

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State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China

School of Automation and Electrical Engineering,Shenyang Ligong University,Shenyang 110158,China

Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang 110169,China

University of Chinese Academy of Sciences,Beijing 100049,China

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National Key R&D Program of ChinaCAS Interdisciplinary Innovation TeamNational Natural Science Foundation of China

2018YFB1304600JCTD-2018-1151775541

2024

中国科学:技术科学(英文版)
中国科学院

中国科学:技术科学(英文版)

CSTPCDEI
影响因子:1.056
ISSN:1674-7321
年,卷(期):2024.67(6)
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