Journal

During the Workshop on the Role of Innovation in the Nuclear Back-End, I joined a panel on harnessing robotics and advanced technologies for safer, more efficient decommissioning activities. We unpacked how autonomous systems and human-robot teaming can accelerate dismantling timelines while maintaining safety margins.

This article surveys the state of the art in variable autonomy for mobile manipulators, with an emphasis on hazardous environments such as nuclear decommissioning, search and rescue, and battery recycling. We synthesise how human-robot teaming strategies adapt autonomy levels to operator workload, communication delays, and mission uncertainty.

We developed a robotic workflow that automates electrochemical impedance spectroscopy (EIS) for electric vehicle batteries. A KUKA KR20 mounted on a 5 m rail cooperates with a custom end-of-arm potentiostat to deliver repeatable connections, measure impedance spectra, and let human operators intervene whenever necessary.

This IEEE Access paper examines where robotics can unlock value in electric vehicle battery disassembly. We model process flows, labour costs, cycle times, safety requirements, and automation readiness to highlight the opportunities—and limits—of deploying robotics at scale.

We presented a semi-autonomous disassembly workflow that overlays mixed reality (MR) instructions onto the workspace, helping operators supervise complex EV battery pack breakdowns while the robot handles routine steps.

This MDPI Robotics article introduces a hybrid task planner that coordinates multiple robotic arms to dismantle electric vehicle battery packs efficiently. The planner fuses logical reasoning with motion planning so that robots can share a workspace without collisions.

The Interfacing Toolbox for Robotic Arms (ITRA) links industrial manipulators, sensors, and actuators to execute EV battery disassembly tasks with hybrid visual servoing. The Batteries journal article showcases deployments on both KUKA KR10 and KR500 platforms.

Presented at ICICIS 2023, this paper analyses how hyperparameter optimisation improves convolutional and CNN-LSTM models for predicting the remaining useful life (RUL) of lithium-ion batteries.