But machines are still wonky at exerting just the right amount of force to control tools that aren’t rigidly attached to their hands. The learned model is obtained using the robot's previous experience, where it disturbs a force torque sensor to figure out how stiff the bubble grippers are. Now, once the robot has sensed the force, it will compare that with the force that the user commands, and maybe say to itself, “it turns out the force that I'm sensing right now is not quite there. During the “squeegee task,” SEED was provided the right amount of force to wipe up some liquid on a plane, where baseline methods struggled to get the right sweep. They will present the work at the IEEE/RSJ International Conference on Intelligent Robots and Systems conference in October.