Researchers use table tennis to understand human-robot dynamics in agile environments !

A team of researchers, led by Matthew Gombolay, an assistant professor in the School of Interactive Computing and director of the Cognitive Optimization and Relational (CORE) Robotics Lab at Georgia Tech, are using the sport of table tennis to showcase that humans may not always trust a robot’s explanation of its intended action.

They have developed what is called a “cobot,” which uses table tennis to demonstrate the potential areas a robot can work closely with human partners to complete tasks.

The robot, Barrett WAM arm equipped with a camera and paddle, was trained through a machine learning process called imitation learning. The researchers developed a system to give the robot positive reinforcement for successful volleys, and negative reinforcement for unsuccessful ones.

“We have also trained our robot to be a safe table tennis partner,” said Gombolay. “We leveraged prior work on table tennis and ‘learning from demonstration techniques’ in which a human can teach a robot a skill such as, how to hit a table tennis shot or simply having the human demonstrate the task to the robot.”

The project demonstrates the potential for robots to work closely with humans in physical and social capacities, a significant step forward for collaborative robotics, according to Gombolay. The development of intelligent systems that can work collaboratively with humans has numerous applications, from manufacturing, health care, to education.