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A HRI study with 31 expert robot operators established that an external viewpoint from an assisting robot could increase teleoperation performance by 14% to 58% while reducing human error by 87% to 100% This video illustrates those findings with a side-by-side comparison of the best and worst viewpoints for the passability and traversability affordances. The passability scenario uses a small unmanned aerial system as a visual assistant that can reach any viewpoint on the idealized hemisphere surrounding the task action. The traversability scenario uses a small ground robot that is restricted to a subset of viewpoints that are reachable. 

This paper develops an autonomous tethered aerial visual assistant for robot operations in unstructured or confined environments. Robotic tele-operation in remote environments is difficult due to the lack of sufficient situational awareness, mostly caused by stationary and limited field-of-view and lack of depth perception from the robot’s onboard camera. The emerging state of the practice is to use two robots, a primary and a secondary that acts as a visual assistant to overcome the perceptual limitations of the onboard sensors by providing an external viewpoint. However, problems exist when using a tele-operated visual assistant: extra manpower, manually chosen suboptimal viewpoint, and extra teamwork demand between primary and secondary operators. In this work, we use an autonomous tethered aerial visual assistant to replace the secondary robot and operator, reducing the human-robot ratio from 2:2 to 1:2. This visual assistant is able to autonomously navigate through unstructured or confined spaces in a risk-aware manner, while continuously maintaining good viewpoint quality to increase the primary operator’s situational awareness. With the proposed co-robots team, tele-operation missions in nuclear operations, bomb squad, disaster robots, and other domains with novel tasks or highly occluded environments could benefit from reduced manpower and teamwork demand, along with improved visual assistance quality based on trustworthy risk-aware motion in cluttered environments.