TY - GEN
T1 - Development of A Walking-Trajectory Measurement System
AU - Tajima, Nina
AU - Kato, Koichiro
AU - Kurokawa, Daigo
AU - Matsuhira, Nobuto
AU - Amano, Kanako
AU - Kato, Yuka
N1 - Funding Information:
This work was supported in part by JSPS Grant-in-Aid for Scientific Research 20K1176 and the Telecommunications Advancement Foundation. We would like to thank for the cooperation of Fukagawa Edo Museum.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/8
Y1 - 2021/8/8
N2 - In recent years, robots have attracted attention to provide a supplemental workforce in Japan as the working population decreases. A reception and response control system using the interface robot ApriPoco™ has been studied, measuring human walking trajectories using a laser range finder, but accurate measurements have been impeded by overlapping people and trajectories leading to missing data. Therefore, in this paper, we propose a system that uses Gaussian process regression to predict human trajectories in addition to the conventional system. Three-directional walking experiments were conducted with groups of one, three, and five people, and the trajectories of the conventional and proposed systems were compared. The experimental results show that the proposed system has fewer missing data than the conventional system and can obtain more accurate trajectories. We also demonstrated human walking-trajectory measurement at a public museum to confirm the effectiveness of this system. In the future, we plan to build a reception system by linking this system with robots.
AB - In recent years, robots have attracted attention to provide a supplemental workforce in Japan as the working population decreases. A reception and response control system using the interface robot ApriPoco™ has been studied, measuring human walking trajectories using a laser range finder, but accurate measurements have been impeded by overlapping people and trajectories leading to missing data. Therefore, in this paper, we propose a system that uses Gaussian process regression to predict human trajectories in addition to the conventional system. Three-directional walking experiments were conducted with groups of one, three, and five people, and the trajectories of the conventional and proposed systems were compared. The experimental results show that the proposed system has fewer missing data than the conventional system and can obtain more accurate trajectories. We also demonstrated human walking-trajectory measurement at a public museum to confirm the effectiveness of this system. In the future, we plan to build a reception system by linking this system with robots.
KW - Gaussian process regression
KW - Human-Robot Interaction
KW - Laser Range Finder
KW - trajectory measurement
UR - http://www.scopus.com/inward/record.url?scp=85115184754&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85115184754&partnerID=8YFLogxK
U2 - 10.1109/ICMA52036.2021.9512592
DO - 10.1109/ICMA52036.2021.9512592
M3 - Conference contribution
AN - SCOPUS:85115184754
T3 - 2021 IEEE International Conference on Mechatronics and Automation, ICMA 2021
SP - 920
EP - 925
BT - 2021 IEEE International Conference on Mechatronics and Automation, ICMA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on Mechatronics and Automation, ICMA 2021
Y2 - 8 August 2021 through 11 August 2021
ER -