Now MIT engineers are aiming to give robots a bit of common sense when faced with situations that push them off their trained path. They’ve developed a method that connects robot motion data with the “common sense knowledge” of large language models, or LLMs. Language taskThe researchers illustrate their new approach with a simple chore: scooping marbles from one bowl and pouring them into another. The algorithm automatically learned to map the robot’s physical coordinates in the trajectories and the corresponding image view to a given subtask. The team then let the robot carry out the scooping task on its own, using the newly learned grounding classifiers.