Human-Robot Interaction (HRI) for collaborative robots has not changed since the introduction of the first cobot. The main interface to communicate with the robot remains a wired display - teach pendant (TP). While attempts are made to make the programming experience better - more intuitive touch-screen displays, it generally remains the same. With the recent rapid development of Augmented Reality (AR), the HRI of the cobot could drastically change. This paper explores AR-based implementations in robotics and categorizes them based on the type of the used device, with the main focus on the least explored category - mobile AR. Furthermore, two experiments are conducted to determine the user's experience in robot programming using TP with a mobile-based AR interface. For this reason, an AR application prototype is developed as a co-interface to a TP. The results of the experiments are presented: the first examines the user's needs that are missing in current solutions, while the second one analyses the user's experience in using the robot with the AR interface. The obtained results suggest that users could benefit from mobile-based AR solutions in the commissioning and troubleshooting phase of the lifetime of the robot. However, at the same time, this solution is not advanced and accurate enough (yet) to encourage users to switch to the new platform and abandon the classical TP, while programming the robot.
|Titel||2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021|
|Status||Udgivet - 2021|
|Begivenhed||30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021 - Virtual, Vancouver, Canada|
Varighed: 8. aug. 2021 → 12. aug. 2021
|Konference||30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021|
|Periode||08/08/2021 → 12/08/2021|
|Navn||IEEE RO-MAN proceedings|
Bibliografisk noteFunding Information:
ACKNOWLEDGMENT This research was conducted in collaboration with Universal Robots, as part of Krzysztof Zielinski’s master’s thesis. This work is part of the project “Energy-efficient Programming of Collaborative Robots” funded by ELFORSK.
© 2021 IEEE.