Human-Inspired Robotic Eye-Hand Coordination Enables New Communication Channels Between Humans and Robots.

This paper concerns human-inspired robotic eye-hand coordination algorithms using custom built robotic eyes that were interfaced with a Baxter robot. Eye movement was programmed anthropomorphically based on previously reported research on human eye-hand coordination during grasped object transportation. Robotic eye tests were first performed on a component level where accurate position and temporal control were achieved. Next, 11 human subjects were recruited to observe the novel robotic system to quantify the ability of robotic eye-hand coordination algorithms to convey two kinds of information to people during object transportation tasks: first, the transported object's delivery location and second, the level of care exerted by the robot to transport the object. Most subjects correlated decreased frequency in gaze fixations on an object's target location with increased care of transporting an object, although these results were somewhat mixed among the 11 human subjects. Additionally, the human subjects were able to reliably infer the delivery location of the transported object purely by the robotic eye-hand coordination algorithm with an overall success rate of 91.4%. These results suggest that anthropomorphic eye-hand coordination of robotic entities could be useful in pedagogical or industrial settings.