ATARI sets to work on robotic disassembly

The EPSRC-funded project - Self-learning robotics for industrial contact-rich tasks (ATARI): enabling smart learning in automated disassembly – is being led by Dr Yongjing Wang from Birmingham’s department of mechanical engineering.

He said ATARI will focus on developing AI-based mechanisms to allow robots to self-learn disassembly tasks and the associated control strategies.

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“The proposed approach is novel in the sense that it provides another perspective into the automation of contact-rich tasks which are currently very much orchestrated and schedule-based,” he said. “With this self-learning capability, we hope the implementation of disassembly automation can be significantly simplified to help the recycling and remanufacturing industry.”

One of ATARI’s challenges will be the development of deep reinforcement learning (DRL) techniques and high-dimension data fusion methods to allow a robot to learn how to be more dextrous.