Robotics, Reinforcement Learning, Machine Learning, Computer Vision, Simulation.
and a new position for the gripper was varied. In the training runs, the gripper could move arbitrarily in 3D space, which made it slightly unrealistic compared to the real world with an actual controller but still provided a rough estimate of how often feedback needs to be provided. Training runs