Vision-Guided Dual-Arm Humanoid Robotic Disassembly of End-of-Life 18650 Lithium-ion Battery Packs
It addresses the need for flexible, fixture-free cell-level disassembly in battery recycling, a practical step toward industrial automation.
The paper presents a vision-guided dual-arm robotic pipeline for disassembling 18650 battery packs from arbitrary poses without fixtures, achieving an 8/10 success rate, 2.4 mm localization error, and 6.0 minutes mean cycle time.
The growing volume of retired lithium-ion battery packs from electric vehicles and portable electronics calls for automated disassembly that is safe, flexible, and selective down to the individual cell. Existing robotic systems, however, mostly assume known pack poses, external fixtures, or specialised tooling, leaving fixture-free cell-level disassembly under pose uncertainty largely unsolved. This paper presents a vision-guided dual-arm pipeline that disassembles a 21-cell 18650 pack from an arbitrary initial pose using only general-purpose parallel-jaw grippers, RGB-D sensing, and a pre-trained grasp detector. Pose uncertainty is absorbed by a learn-and-filter perception stack with discrete look-and-move wrist-camera corrections, while a mid-task support transfer between the two arms extends the effective workspace without any external clamp. The pipeline achieves an 8/10 end-to-end success rate, a cell-localisation root-mean-square error of $2.4$\,mm, and a mean cycle time of 6.0\,minutes per pack, providing a practical, fixture-free building block for industrial battery recycling.