Toward Human-like Teleoperated Robot Motion: Performance and Perception of a Choreography-inspired Method in Static and Dynamic Tasks for Rapid Pose Selection of Articulated Robots

In some applications, operators may want to create fluid, human-like motion on a remotely-operated robot, for example, a device used for remote telepresence. This paper examines two methods of controlling the pose of a Baxter robot via an Xbox One controller. The first method is a joint- by-joint (JBJ) method in which one joint of each limb is specified in sequence. The second method of control, named Robot Choreography Center (RCC), utilizes choreographic abstractions in order to simultaneously move multiple joints of the limb of the robot in a predictable manner. Thirty-eight users were asked to perform four tasks with each method. Success rate and duration of successfully completed tasks were used to analyze the performances of the participants. Analysis of the preferences of the users found that the joint-by-joint (JBJ) method was considered to be more precise, easier to use, safer, and more articulate, while the choreography-inspired (RCC) method of control was perceived as faster, more fluid, and more expressive. Moreover, performance data found that while both methods of control were over 80% successful for the two static tasks, the RCC method was an average of 11.85% more successful for the two more difficult, dynamic tasks. Future work will leverage this framework to investigate ideas of fluidity, expressivity, and human-likeness in robotic motion through online user studies with larger participant pools.