Dynamic Path Visualization for Human-Robot Collaboration

Augmented reality technology can enable robots to visualize their future actions giving users crucial information to avoid collisions and other conflicting actions. Although a robot's entire action plan could be visualized (such as the output of a navigational planner), how far into the future it is appropriate to display the robot's plan is unknown. We developed a dynamic path visualizer that projects the robot's motion intent at varying lengths depending on the complexity of the upcoming path. We tested our approach in a virtual game where participants were tasked to collect and deliver gems to a robot that moves randomly towards a grid of markers in a confined area. Preliminary results on a small sample size indicate no significant effect on task performance; however, open-ended responses reveal participants preference towards visuals that show longer path projections.

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Dynamic Path Visualization for Human-Robot Collaboration

Semantic Scholar · Computer Science · 2021

Abstract

Augmented reality technology can enable robots to visualize their future actions giving users crucial information to avoid collisions and other conflicting actions. Although a robot's entire action plan could be visualized (such as the output of a navigational planner), how far into the future it is appropriate to display the robot's plan is unknown. We developed a dynamic path visualizer that projects the robot's motion intent at varying lengths depending on the complexity of the upcoming path. We tested our approach in a virtual game where participants were tasked to collect and deliver gems to a robot that moves randomly towards a grid of markers in a confined area. Preliminary results on a small sample size indicate no significant effect on task performance; however, open-ended responses reveal participants preference towards visuals that show longer path projections.

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