Tool Compensation and User Strategy during Human-Robot Teleoperation are Impacted by System Dynamics and Kinesthetic Feedback

TL;DR

It is found that while tracking performance at the follower port was similar across transmissions, users' adjustment at the leader port differed between Rigid and EM transmissions, suggesting that tracking strategy does change between dynamics and feedback.

Abstract

Manipulating an environment remotely with a robotic teleoperator introduces novel electromechanical (EM) dynamics between the user and environment. While considerable effort has focused on minimizing these dynamics, there is limited research into understanding their impact on a user's internal model and resulting motor control strategy. Here we investigate to what degree the dynamics and kinesthetic feedback of the teleoperator influence task behavior and tool compensation. Our teleoperator testbed features a leader port controlled by user input via wrist rotation, a follower port connected to a virtual environment rendered by rotary motor, and three distinct transmissions (Rigid, Unilateral EM, Bilateral EM) in-between that can be engaged independently. 30 adult participants rotated a disk in a visco-elastic virtual environment through counterbalanced presentation of each transmission. Users tracked targets oscillating at 7 pre-defined random frequencies between 0.55 and 2.35 Hz. After session completion, trajectories of the target, leader, and follower were decomposed into components of gain and phase error for all frequencies. We found that while tracking performance at the follower port was similar across transmissions, users' adjustment at the leader port differed between Rigid and EM transmissions. Users applied different pinch forces between Rigid and Unilateral transmissions, suggesting that tracking strategy does change between dynamics and feedback. However, the users' ability to compensate dynamics diminished significantly as task speed got faster and more difficult. Therefore, there are limits to pursuit tracking at the human wrist when compensating teleoperator dynamics.

Figures (15)

• Figure 1: A general overview of the teleoperator testbed Singhala2021ADynamics. The user interacted through a grip interface attached to the leader side (circled L), and the environment was rendered by a motor attached to the follower side (circled F). A steel rod forms the direct rigid transmission when coupled, whereas an additional motor pair in the transmission region (circled T) provides electromechanical transmission for unilateral and bilateral forcing when coupled. (The elastic and damping transmissions in the background were decoupled and ignored for this experiment.)
• Figure 2: While the user controls the grip interface with their wrist during a tracking task, any potential sight of the testbed mechanics was obscured by a rigid opaque barrier fastened underneath the task monitor and around the input shaft. This way, visual confounds were mitigated without impacting the motion of the wrist.
• Figure 3: A graphical summary of all notable components of the human-device interaction system during the teleoperation study. Green arrows generally indicate electronic signal flows. Dashed link arrows highlight connections that can be toggled.
• Figure 4: The protocol progression for a typical session. Note how training speeds need only two trials, whereas other task speed subblocks need four trials.
• Figure 5: An example display of object-tracking at two points in time, the initial object positions in solid color and the projected positions in faded color. As the ball followed a path indicated by the red arrow, the user attempted to match the positon of the ball as indicated by the blue arrow. The viscoelastic disk is the gray circle in the background.