Effects of Mobile Robot Passing-Motion Path Curvature on Human Affective States in a Hallway Environment

Abstract

Abstract For social robots to move in ways that are socially desirable to the people that they encounter, it is necessary to understand the types of robot motions that people find more or less appealing. An experiment was conducted in which participants ( $$N=20$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>=</mml:mo> <mml:mn>20</mml:mn> </mml:mrow> </mml:math> ) encountered a mobile robot in a virtual reality hallway environment. The robot passed them following trajectories shaped like cubic Bezier curves. The sharpness of curvature of the robot motions was varied, as was the distance from the person at which the passing-motion was initiated. Participants scored each motion both on how arousing and pleasurable they found the experience of being passed by the robot to determine the affective state induced by the robot motion. Our data show that the curvature of passing-motions has an effect on the affective state of the person being passed, while other proxemic constraints are held constant. Participants respond more positively to paths that have moderate curvature, and more negatively to passing-motions that are either too sharply curved, or too straight. This finding enables the development of path planning algorithms that respect the empirically–defined path curvature constraint to improve human acceptability in this context.