The Challenges of Using Robots to Automate the Recycling of Electronic Devices

Abstract

This paper tackles the challenges of automating battery removal from small electronic devices, such as heat cost allocators and smoke detectors. The process is critical for mitigating fire hazards caused by lithium batteries in recycling facilities and for supporting a circular economy. We focus on advanced methodologies and robotic technologies designed to overcome the significant hurdles posed by the diverse range of device designs, complex battery compartments, and varying states of damage. Our approach integrates Vision-Language Models (VLMs) for real-time, adaptive disassembly planning, computer vision, tactile skills, soft robotics, and reconfigurable robotic workcells to enhance perception, dexterity, and adaptability in handling diverse device designs and damage states. Additionally, a reconfigurable robotic workcell with modular hardware and standardized interfaces enables seamless adaptation to various devices. Laboratory testing demonstrates improved efficiency and reduced manual intervention, highlighting the potential of AI-driven, reconfigurable robotics for scalable and sustainable e-waste recycling.