Washington, Feb 12: Being in someone else’s shoes can help us to learn what makes them tick, an approach being tried out to promote better understanding between humans and robots so that they can work as a team.
“People aren’t robots, they don’t do things the same way every single time,” says Julie Shah, assistant professor of aeronautics and astronautics at MIT, who led the study.
“And so there is a mismatch between the way we programme robots to perform tasks in exactly the same way each time and what we need them to do if they are going to work in concert with people,” adds Shah.
So Shah and MIT doctoral student Stefanos Nikolaidis began to investigate whether techniques that have been shown to work well in training people could also be applied to mixed teams of humans and robots, according to an MIT statement.
One such technique, known as cross-training, sees team members swap roles with each other on given days. “This allows people to form a better idea of how their role affects their partner and how their partner’s role affects them,” Shah says.
Shah and Nikolaidis found that the period in which human and robot were working at the same time – known as concurrent motion – increased by 71 percent in teams that had taken part in cross-training.
They also found that the amount of time the humans spent doing nothing – while waiting for the robot to complete a stage of the task, for example – decreased by 41 percent.
What’s more, when the pair studied the robots themselves, they found that the learning algorithms recorded a much lower level of uncertainty about what their human teammate was likely to do next – a measure known as the entropy level – if they had been through cross-training.
“This is the first evidence that human-robot teamwork is improved when a human and robot train together by switching roles, in a manner similar to effective human team training practices,” Nikolaidis says.
These findings will be presented at the International Conference on Human-Robot Interaction in Tokyo in March.