TY - GEN
T1 - Electrifying Obstacle Avoidance
T2 - 2nd International Conference on Hybrid Human-Artificial Intelligence, HHAI 2023
AU - Shahu, Ambika
AU - Kassem, Khaled
AU - Zehetgruber, Leonhard
AU - Wintersberger, Philipp
AU - Michahelles, Florian
N1 - Publisher Copyright:
© 2023 The Authors.
PY - 2023/6/22
Y1 - 2023/6/22
N2 - 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.
AB - 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.
KW - Electrical muscle stimulation
KW - Human-in-the-loop
KW - Human-robot collaboration
KW - Robot
KW - Teleoperation
KW - User study
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85171422195&partnerID=8YFLogxK
U2 - 10.3233/FAIA230086
DO - 10.3233/FAIA230086
M3 - Conference contribution
AN - SCOPUS:85171422195
T3 - Frontiers in Artificial Intelligence and Applications
SP - 224
EP - 233
BT - HHAI 2023
A2 - Lukowicz, Paul
A2 - Mayer, Sven
A2 - Koch, Janin
A2 - Shawe-Taylor, John
A2 - Tiddi, Ilaria
PB - IOS Press BV
Y2 - 26 June 2023 through 30 June 2023
ER -