TY - GEN
T1 - Self-Supervised Button Recognition for Indoor Mobile Robots
AU - Pyo, Jeong Won
AU - Lee, Kwang Hee
AU - Cho, Jung San
AU - Kuc, Tae Yong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In recent years, with the rapid advances in technology, the precision and accuracy of indoor autonomous driving have also improved remarkably. However, despite the development of these technologies, there are still many difficulties to perform services through real mobile robots. In this paper, we focused on the mobile robot that drives in multiple spaces in a multi-story building using an elevator. In order to operate the elevator, the mobile robot must be able to operate by pressing the elevator button itself. To solve this problem, in this paper, we propose self-supervised button recognition. We created fake buttons for self-supervised learning and placed these on random backgrounds to increase the diversity of the dataset. In addition, the generated realistic buttons are re-generated like real buttons through a GAN. In experiments, we presented that our self-supervised button recognition was performed in an actual environment without separate labeling.
AB - In recent years, with the rapid advances in technology, the precision and accuracy of indoor autonomous driving have also improved remarkably. However, despite the development of these technologies, there are still many difficulties to perform services through real mobile robots. In this paper, we focused on the mobile robot that drives in multiple spaces in a multi-story building using an elevator. In order to operate the elevator, the mobile robot must be able to operate by pressing the elevator button itself. To solve this problem, in this paper, we propose self-supervised button recognition. We created fake buttons for self-supervised learning and placed these on random backgrounds to increase the diversity of the dataset. In addition, the generated realistic buttons are re-generated like real buttons through a GAN. In experiments, we presented that our self-supervised button recognition was performed in an actual environment without separate labeling.
KW - elevator
KW - GAN
KW - object recognition
KW - self-supervised
UR - https://www.scopus.com/pages/publications/85146714005
U2 - 10.1109/SCISISIS55246.2022.10002017
DO - 10.1109/SCISISIS55246.2022.10002017
M3 - Conference contribution
AN - SCOPUS:85146714005
T3 - 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022
BT - 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022
Y2 - 29 November 2022 through 2 December 2022
ER -