Electrifying Obstacle Avoidance: Enhancing Teleoperation of Robots with EMS-Assisted Obstacle Avoidance

Abstract

We investigate how the use of haptic feedback through electrical muscle stimulation (EMS) can improve collision-avoidance in a robot teleoperation scenario. Background: Collision-free robot teleoperation requires extensive situation awareness by the operator. This is difficult to achieve purely visually when obstacles can exist outside of the robot's field of view. Therefore, feedback from other sensory channels can be beneficial. Method: We compare feedback modalities in the form of auditory, haptic and bi-modal feedback, notifying users about incoming obstacles outside their field of view, and moving their arms in the direction to avoid the obstacle. We evaluate the different feedback modalities alongside a unimodal visual feedback baseline in a user study (N=9), where participants are controlling a robotic arm in a virtual reality environment. We measure objective performance metrics in terms of the number of collisions and errors, as well as subjective user feedback using the NASA-TLX and the short version of the User Experience Questionnaire. Findings: Unimodal EMS and bi-modal feedback outperformed the baseline and unimodal auditory feedback when it comes to hedonic user experience (p<.001). EMS outperformed the baseline with regards to pragmatic user experience (p=.018). We did not detect significant differences in the performance metrics (collisions and errors). We measured a strong learning effect when investigating the collision count and time. Key insights: The use of EMS is promising for this task. Two of the nine participants reported to experience some level of discomfort. The modality is best utilized for nudging rather than extended movement.