退役电池回收中不确定拆卸的人机协同再制造

Hao Yin, Jinhua Xiao, Guoxian Wang
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引用次数: 2

摘要

新能源汽车的生产和销售带来了退役电动汽车电池的回收需求,实现了资源的可持续和绿色利用。本文的目的是为柔性生产车间中电动汽车电池的不确定拆卸提供解决方案。针对电动汽车电池回收过程中拆卸和再制造过程不确定的问题,提出了一种新型的人机协同柔性再制造系统。分析了拆卸过程中的不确定性,建立了人机协作拆卸系统的体系结构。采用D-H参数法对协作机器人及其控制系统进行运动学分析。采用快速探索随机树(RRT)算法进行协作机器人的轨迹规划。采用神经网络YOLOv7算法支持基于深度视觉的系统,提高了拆卸过程的识别精度和运动精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human-Robot Collaboration Re-Manufacturing for Uncertain Disassembly in Retired Battery Recycling
The production and sales of new energy vehicles has brought the recycling needs of retired Electric Vehicle (EV) battery for sustainable and green resource utilization. The purpose of this paper is to provide solutions for uncertain disassembly of EV battery in flexible production workshops. In this paper, a novel human-robot collaborative flexible re-manufacturing system is proposed to deal with the difficulties for the uncertain disassembly and re-manufacturing process of EV-battery recycling. The uncertainty in the disassembly process are analyzed to build the architecture of human-robot collaboration disassembly system. The D-H parameter method was used to analyze the kinematics of collaboration robot and its control system. The trajectory planning of collaboration robot is performed using the Rapidly-exploring Random Tree (RRT) algorithm. The neural network YOLOv7 algorithm is used to support the depth vision-based system to improve the recognition accuracy and motion accuracy for disassembly process.
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