Here is how AI can enhance infrastructure

Xiao Liang and Minghui Zheng in their lab.

Assistant Professor Xiao Liang is leading research that uses robot-assisted disassembly in structural health monitoring to increase productivity, while enhancing job satisfaction and ensuring worker safety.

Guiding human-robot collaboration with artificial intelligence

Liang and his team will perform fundamental studies on collaborative disassembly systems for end-of-use products. The project focuses on five interdependent research tasks within the context of future technology, future worker and future work: work environment monitoring with human motion prediction; planning, learning and control for collaborative robots; disassembly sequence planning under uncertainty and exploring human robot collaboration (HRC)-inspired design guidelines; human-robotics systems integration; and modeling and prediction of economic impacts of HRC in remanufacturing environments.

Repurposing electronic waste

UB will conduct work environment monitoring with human motion prediction and planning, learning and control for collaborative robots. This research deals specifically with electronic waste such as used computers and mobile devices. According to Liang, the benefits of this project expand beyond tradition environmental impacts. “Besides the obvious environmental inspiration, such as consumer interest in green products and scarcity of resources, potential profiles from salvaging valuable materials and components have motivated the consideration of end-of-use-product recovery and remanufacturing,” Liang says.

Xiao Liang.
Lead Researcher:

Xiao LiangAssistant Professor, Department of Civil, Structural and Environmental Engineering, School of Engineering and Applied Sciences