Authors: Hannah Baez; Naomi Harrison; Justine Roy; Thomas Schweich; Brandon Navarro; Ajay Manohar
Advisors: Zhi Li; Carlo Pinciroli; Maqsood Ali Mughal
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.
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