The booming of electric vehicles demands efficient battery disassembly for recycling to be environment-friendly. Due to the unstructured environment and high uncertainties, battery disassembly is still primarily done by humans, probably assisted by robots. It is highly desirable to design autonomous solutions to improve work efficiency and lower human risks in high voltage and toxic environments. This paper proposes a novel framework of the NeuroSymbolic task and motion planning method to disassemble batteries in an unstructured environment using robots automatically. It enables robots to independently locate and disassemble battery bolts, with or without obstacles. This study not only provides a solution for intelligently disassembling electric vehicle batteries but also verifies its feasibility through a set of test results with the robot accomplishing the disassembly tasks in a complex and dynamic environment.

翻译：电动车辆的繁荣要求高效的电池拆卸,以便进行再循环,这是对环境无害的。由于环境不结构,不确定因素很大,电池拆解仍然主要由人进行,很可能由机器人协助。非常可取的是设计自主的解决办法,以提高高压和有毒环境中的工作效率和降低人类风险。本文提出了神经循环任务和运动规划方法的新框架,以便用机器人自动在无结构的环境中拆解电池。它使机器人能够独立地找到和拆解电池栓,无论是否有障碍。这项研究不仅为明智地拆解电动车辆电池提供了解决办法,而且还通过一套测试结果来验证其可行性,即机器人在一个复杂和动态的环境中完成拆解任务。