When robots come across unfamiliar objects, they struggle to account for a simple truth: Appearances aren’t everything. They may attempt to grasp a block, only to find out it’s a literal piece of cake. The misleading appearance of that object could lead the robot to miscalculate physical properties like the object’s weight and center of mass, using the wrong grasp and applying more force than needed.To see through this illusion, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers designed the Grasping Neural Process, a predictive physics model capable of inferring…
