The Globe Digest #63: Robotic system zeroes in on objects most relevant for helping humans

Globe Digest #63 – Relevance: The Future of Helpful Robots

In Globe Digest #63, explore how MIT’s new robotic framework “Relevance” helps machines understand what humans need — fast, intuitively, and safely.

For a robot, the real world is a lot to take in. Making sense of every data point in a scene can take a huge amount of computational effort and time. Using that information to then decide how to best help a human is an even thornier exercise.

Now, MIT roboticists have a way to cut through the data noise, to help robots focus on the features in a scene that are most relevant for assisting humans.

Their approach, which they aptly dub “Relevance,” enables a robot to use cues in a scene, such as audio and visual information, to determine a human’s objective and then quickly identify the objects that are most likely to be relevant in fulfilling that objective.