Machines in industrial workplace environments have notoriously been a source of harm for human health. Machines in gyms, instead, can help improve both health and fitness. This observation has been the starting point for this project. As people make use of machines in gyms or similar exercise setups to improve their health, why not take inspiration from that and develop machines for the factory floor that do the same?
This project leverages sensor-based technologies to monitoring human physique, condition, and behavior in real time to dynamically adjust to these differences for physical collaboration between a human worker and a robot in industrial workplace environments.
The Gymnast_CoBot approach does not attempt to replace the human worker. Rather, our goal is to leverage robotic technology to tweak work routines in an industrial environment to be more sustainable for a human worker’s physical condition. By allowing the robot to handle physical tasks with potentially dangerous long-term implications, such as heavy lifting and straining postures, the worker can focus on performing operations that are otherwise challenging for robots, like navigating cluttered spaces to correctly allocate items.
Team: Kristian Kloeckl (PI), Taskin Padir (PI), Rui Luo, Patrick Dawson, Mark Zolotas, Zuozheng Zhong, Dipanjan Saha, Salah Bazzi. This work was supported by the National Science Foundation.