• Energy Research

This review examines the robotic disassembly of electric vehicle batteries, a critical concern as the adoption of electric vehicles increases worldwide. This work provides a comprehensive overview of the current state of the art in robotic disassembly and outlines future directions for research and policy in this essential area. The study highlights the urgent need for sustainable management practices to mitigate the environmental impact of end-of-life batteries. It evaluates current robotic technologies, strategies for human–robot collaboration, and the role of artificial intelligence in enhancing the efficiency and safety of these processes. The investigation identifies significant challenges, including the absence of standardised designs and the inherent risks of handling batteries. The feasibility of adopting design-for-disassembly principles is explored as a way to improve recycling and repurposing efforts. The review suggests avenues for future research, focusing on developing advanced robotics solutions and establishing supportive regulatory frameworks. These efforts aim to foster sustainable practices in the lifecycle management of electric vehicle batteries, contributing to the broader goal of environmental sustainability in the electric vehicle and battery industries. Previous reviews generally focus on recycling electric vehicle battery chemistry and materials; this review complements previous research by focusing on robotised disassembly.

The paper introduces a robotic manipulation framework suitable for the execution of manipulation tasks. Based on the ROS platform, the framework provides advanced motion planning and control functionalities for robotic systems to guarantee a high level of autonomy during the execution of an action. The integrated motion planning module can handle multiple motion planners to generate collision-free trajectories for a given planning scene that can be dynamically uploaded. In the same way, the robot controllers can be changed online on the base of the robot behavior required by the action under execution. The motion control of the robotic system is fully demanded to the manipulation framework relieving the upper control layers from the management of low-level functionalities and the task geometrical information. The framework can be used downstream to a task planner or as a standalone library to simplify the robot programming in complex manipulation tasks.