Robots Learn to Identify Objects by 'Blindly' Feeling Them
Researchers from MIT, Amazon Robotics, and the University of British Columbia have developed a new technique enabling robots to learn an object's weight, softness, or contents using only internal sensors—no cameras or external tools needed. By picking up and gently shaking an object, the robot infers properties like mass and softness. The technique uses simulations of the robot and object, analyzing data from the robot's joint encoders to work backward and identify object properties. This low-cost method is particularly useful in environments where cameras are ineffective (like dark basements or post-earthquake rubble) and is robust in handling unseen scenarios. Published at the International Conference on Robotics and Automation, this research promises to improve robot learning, enabling faster development of manipulation skills and adaptation to changing environments.