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Drones can provide a minimally-constrained adapting camera view to supportrobot telemanipulation. Furthermore, the drone view can be automated to reducethe burden on the operator during teleoperation. However, existing approachesdo not focus on two important aspects of using a drone as an automated viewprovider. The first is how the drone should select from a range of qualityviewpoints within the workspace (e.g., opposite sides of an object). The secondis how to compensate for unavoidable drone pose uncertainty in determining theviewpoint. In this paper, we provide a nonlinear optimization method thatyields effective and adaptive drone viewpoints for telemanipulation with anarticulated manipulator. Our first key idea is to use sparse human-in-the-loopinput to toggle between multiple automatically-generated drone viewpoints. Oursecond key idea is to introduce optimization objectives that maintain a view ofthe manipulator while considering drone uncertainty and the impact on viewpointocclusion and environment collisions. We provide an instantiation of our droneviewpoint method within a drone-manipulator remote teleoperation system.Finally, we provide an initial validation of our method in tasks where wecomplete common household and industrial manipulations.

A Method For Automated Drone Viewpoints to Support Remote Robot Manipulation