[2205.07441] Autonomous Electric Vehicle Battery Disassembly Based on NeuroSymbolic Computing
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Computer Science > Robotics

arXiv:2205.07441 (cs)
[Submitted on 16 May 2022]

Title:Autonomous Electric Vehicle Battery Disassembly Based on NeuroSymbolic Computing

Authors:Hengwei Zhang, Hua Yang, Haitao Wang, Zhigang Wang, Shengmin Zhang, Ming Chen
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Abstract: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.
Comments: Accepted to IntelliSys 2022(Intelligent Systems Conference),15 pages with 6 figures
Subjects: Robotics (cs.RO)
ACM classes: I.2.9
Report number: CONF-220910
Cite as: arXiv:2205.07441 [cs.RO]
  (or arXiv:2205.07441v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2205.07441

Submission history

From: Hengwei Zhang [view email]
[v1] Mon, 16 May 2022 04:32:53 UTC (4,356 KB)
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