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Do you manage to walk a crowded street without bumping into people or having near misses as you try to pass? If so you probably learned how to do it in a very similar way to this socially aware robot, by reinforcement learning.
With the deployment of wheeled robots, see Delivery Robots Becoming A Reality, the sharing of the walkways with robots is becoming an important topic. We humans, assuming your not a robot, have managed to evolve mechanisms for sharing the narrow strip available for movement. What is more interesting is that we haven’t formalised the rules that we have invented. They are what you might call “social” rules and most of the time they do keep the traffic flowing and minimize collisions.
It is obvious we have to teach our wheeled robots these social rules, but the problem is what exactly are they? Researchers at MIT decided to side step the whole issue by using reinforcement learning to let the robots learn the rules for themselves:
For robotic vehicles to navigate safely and efficiently in pedestrian-rich environments, it is important to model subtle human behaviors and navigation rules.
