Supervisory control of a humanoid robot in a manipulation task requires coordination of remote perception with robot action, which becomes more demanding with multiple moving cameras available for task supervision. We explore the use of autonomous camera control and selection to reduce operator workload and improve task performance in a supervisory control task. We design a novel approach to autonomous camera selection and control, and evaluate the approach in a user study which revealed that autonomous camera control does improve task performance and operator experience, but autonomous camera selection requires further investigation to benefit the operator’s confidence and maintain trust in the robot autonomy.

Telepresence tele-action robots enable human workers to reliably perform difficult tasks in remote, cluttered, and human environments. However, the effort to control coordinated manipulation and active perception motions may exhaust and intimidate novice workers. We hypothesize that such cognitive efforts would be effectively reduced if the teleoperators are provided with autonomous camera selection and control aligned with the natural perception-action coupling of the human motor system. Thus, we conducted a user study to investigate the coordination of active perception control and manipulation motions performed with visual feedback from various wearable and standalone cameras in a telepresence scenario. Our study discovered rich information about telepresence camera selection to inform telepresence system configuration and possible teleoperation assistance design for reduced cognitive effort in robot teleoperation.