A method of training a robot to autonomously execute a robotic task includes moving an end effector through multiple states of a predetermined robotic task to demonstrate the task to the robot in a set of n training demonstrations. The method includes measuring training data, including at least the linear force and the torque via a force-torque sensor while moving the end effector through the multiple states. Key features are extracted from the training data, which is segmented into a time sequence of control primitives. Transitions between adjacent segments of the time sequence are identified. During autonomous execution of the same task, a controller detects the transitions and automatically switches between control modes. A robotic system includes a robot, force-torque sensor, and a controller programmed to execute the method.
Rapid robotic imitation learning of force-torque tasks