TY - GEN
T1 - Remote Robot Control with Low-cost Robotic Arms and Human Motions
AU - Fogg, Jordan
AU - Deng, Zeyu
AU - Meursing, Emory
AU - Huang, Long
AU - Wang, Huaxia
AU - Wang, Chen
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2023/4/24
Y1 - 2023/4/24
N2 - Geographically-separated people are now connected by smart devices and networks to enjoy remote human interactions. However, current online interactions are still confined in a virtual space. Extending the pure virtual interactions to the physical world requires multidisciplinary research efforts, including sensing, robot control, networking, and kinematics mapping. This paper introduces a remote motion-controlled robotic arm framework by integrating these techniques, which allows a user to control a far-end robotic arm simply by hand motions. In the meanwhile, the robotic arm follows the user's hand to perform tasks and sends back its live states to the user in video stream. Furthermore, we explore using cheap robotic arms and off-the-shelf motion capture devices to facilitate the wide use of the platform in people's daily life. No professional knowledge is required from the user. Moreover, we implement a testbed that connects two US states for the remote control study. We investigate different types of latency that affect the user's remote control experience and conduct comparative studies. Results show that the current commercial motion capture device, low-cost robotic arms and networks are already available to provide physically-augmented remote human interactions.
AB - Geographically-separated people are now connected by smart devices and networks to enjoy remote human interactions. However, current online interactions are still confined in a virtual space. Extending the pure virtual interactions to the physical world requires multidisciplinary research efforts, including sensing, robot control, networking, and kinematics mapping. This paper introduces a remote motion-controlled robotic arm framework by integrating these techniques, which allows a user to control a far-end robotic arm simply by hand motions. In the meanwhile, the robotic arm follows the user's hand to perform tasks and sends back its live states to the user in video stream. Furthermore, we explore using cheap robotic arms and off-the-shelf motion capture devices to facilitate the wide use of the platform in people's daily life. No professional knowledge is required from the user. Moreover, we implement a testbed that connects two US states for the remote control study. We investigate different types of latency that affect the user's remote control experience and conduct comparative studies. Results show that the current commercial motion capture device, low-cost robotic arms and networks are already available to provide physically-augmented remote human interactions.
UR - https://www.scopus.com/pages/publications/85158954701
UR - https://www.scopus.com/pages/publications/85158954701#tab=citedBy
U2 - 10.1145/3544793.3560331
DO - 10.1145/3544793.3560331
M3 - Conference contribution
AN - SCOPUS:85158954701
T3 - UbiComp/ISWC 2022 Adjunct - Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers
SP - 32
EP - 34
BT - UbiComp/ISWC 2022 Adjunct - Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers
PB - Association for Computing Machinery, Inc
T2 - 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2022
Y2 - 11 September 2022 through 15 September 2022
ER -