Activity-Segmentation

The paper proposes a method using motion and tactile features to automatically segment atomic actions from teleoperated demonstrations for complex robotic tasks, provides a dataset of pick-and-place teleoperation with a dexterous hand, and shows the proposed features generalize between episodes and similar objects while tactile sensing improves activity recognition within demonstrations.

Modern service robots are provided with one or more sensors, often including RGB-D cameras, to perceive objects and humans in the …