The automotive industry is involved in a massive transformation from standard endothermic engines to electric propulsion. The core element of the Electic Vehicle (EV) is the battery pack. Battery pack production misses regulations concerning manufacturing standards and safety-related issues. In such a fragmented scenario, the increasing number of EVs in circulation is growing exponentially, opening new challenges for managing the End-of-Life (EoL) of their battery packs. This paper analyses the use of robotics for EVs’ battery pack disassembly to enable the extraction of the battery modules preserving their integrity for further reuse or recycling. The analysis highlights that a complete automatic disassembly remains difficult, while human-robot collaborative disassembly guarantees high flexibility and productivity. The paper introduces guidelines for designing a robotic cell to disassemble a battery pack with the support of an operator. The design of the workcell evaluates the technological requirements for disassembly, the analysis of potentially explosive atmospheres (ATEX) of the area around the battery pack, and the design and optimisation of robotics tools in the ATEX zone. The work proposes solutions according to the current international standards.

The paper deals with the generation of optimal trajectories for industrial robots in machining and additive manufacturing applications. The proposed method uses an Ant Colony algorithm to solve a kinodynamic motion planning problem. It exploits the kinematic redundancy that is often present in these applications to optimize the execution of trajectory. At the same time, the robot kinematics and dynamics constraints are respected and robot collisions are avoided. To reduce the computational burden, the task workspace is discretized enabling the use of efficient network solver based on Ant Colony theory. The proposed method is validated in robotic milling and additive manufacturing real-world scenarios.