基于行为树模型的电动汽车电池组件分类机器人系统框架

Robotic System Framework for Battery Components Classification of Electric Vehicles Based on Behavior Tree Model

针对回收电动汽车电池时必须拆卸和分类电池组件的问题,提出了一种实现电动汽车电池组件半自动化拆卸和分类的移动机器人系统。该系统利用行为树模型来执行认知和监控任务,以模块化的方式集成不同的机器人能力,如导航、目标跟踪、运动规划和抓取。在静态和动态环境下对该系统框架进行了仿真测试,并根据机器人完成任务的时间和成功率对其进行评估。结果表明:机器人在静态和动态环境下完成电池组件分类任务的平均时间分别为51.63min和83.09min,总体成功率分别为95%和82%,验证了所提机器人系统的有效性,具有高效率和高成功率的性能。

A mobile robotic system to achieve semi-automatic disassembly and sorting of electric vehicle battery components is proposed to address the problem of having to disassemble and classification of the battery components when recycling electric vehicle batteries.The system utilizes a behavior tree model to perform cognitive and monitoring tasks,integrating different robotic capabilities such as navigation,target tracking,motion planning and grasping in a modular way.The system framework was tested in simulation in both static and dynamic environments,and the robot was evaluated based on its time and success rate in completing tasks.The results show that the average time for the robot to complete the classification of the battery components in static and dynamic environments is 51.63min and 83.09min,respectively,and the overall success rate is 95%and 82%,respectively,which verifies the effectiveness of the proposed robotic system with high efficiency and high success rate performance.