TY - GEN
T1 - Intelligent Control for Illuminance Measurement by an Autonomous Mobile Robot
AU - Inoue, R.
AU - Arai, T.
AU - Toda, Y.
AU - Tsujimoto, M.
AU - Taniguchi, K.
AU - Kubota, N.
PY - 2019/10
Y1 - 2019/10
N2 - Over the last decade, the labor shortage suffers various industry sectors due to declining birthrate and aging population. Thus, autonomous robots have been widely researched for overcoming the labor-shortage phenomena. The construction sector is one of the industries that require high manpower to conduct various tasks. Traditional illuminance measurement in construction sites is one of the tasks that require much manpower and consumption time. As such, the development of various robots has been conducted to autonomously measure construction sites' illuminance. In this paper, we develop an autonomous mobile robot to perform illuminance measurement while performing simultaneous localization and mapping (SLAM), and obstacle avoidance. Human operators first set a navigation path and send it to the robot. With the given path, the robot starts to navigate the environment autonomously and measures the illuminance of the target points in the environment. The robot is validated through several experiments conducted in real-world indoor environments. Experimental results showed that the robot was able to autonomously measure the illuminance of the environment.
AB - Over the last decade, the labor shortage suffers various industry sectors due to declining birthrate and aging population. Thus, autonomous robots have been widely researched for overcoming the labor-shortage phenomena. The construction sector is one of the industries that require high manpower to conduct various tasks. Traditional illuminance measurement in construction sites is one of the tasks that require much manpower and consumption time. As such, the development of various robots has been conducted to autonomously measure construction sites' illuminance. In this paper, we develop an autonomous mobile robot to perform illuminance measurement while performing simultaneous localization and mapping (SLAM), and obstacle avoidance. Human operators first set a navigation path and send it to the robot. With the given path, the robot starts to navigate the environment autonomously and measures the illuminance of the target points in the environment. The robot is validated through several experiments conducted in real-world indoor environments. Experimental results showed that the robot was able to autonomously measure the illuminance of the environment.
UR - http://www.scopus.com/inward/record.url?scp=85078330338&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078330338&partnerID=8YFLogxK
U2 - 10.1109/ARSO46408.2019.8948806
DO - 10.1109/ARSO46408.2019.8948806
M3 - Conference contribution
AN - SCOPUS:85078330338
T3 - Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO
SP - 270
EP - 274
BT - 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019
PB - IEEE Computer Society
T2 - 15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019
Y2 - 31 October 2019 through 2 November 2019
ER -