Advancing student interaction with a learning robot: Digital twin, connectivity, and augmented reality

During interaction with learning robots, students often experience difficulties understanding the robot intent and its practical realization. To address this challenge, we propose a connected environment that integrates the robot, its digital twin and virtual sensors. The environment supports digital experiments that enable the physical robot to determine optimal policy for performing a manipulation task. This can potentially make the robot learning process transparent for students using augmented reality tools. Implementation of the proposed approach for the case of weightlifting by humanoid robot is