TY - GEN
T1 - Basic Experiments for a Remote Control Robot-Mapping System in Complex Environment
AU - Ke, Li
AU - Song, Tingxin
AU - Pinrath, Nattawat
AU - Yee, Darren Phang Ren
AU - Matsuhira, Nobuto
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Simultaneous localization and mapping (SLAM) constitutes the core challenge in autonomous navigation while avoiding obstacles for mobile robots. Traditional robots require close-range operators during mapping, and remote control remains difficult in a complex environment. Furthermore, the height of sensors limits the detection of small obstacles in 2D mapping. This paper presents a robot system that solves these problems. The system operates SLAM remotely, navigates narrow paths, and estimates the location of small obstacles beyond the detection range of 2D lidar. The experiments utilized the Robot Operating System and an open source GMapping software package. Lidar, a camera, and an inertial measurement sensor unit enabled the remote monitoring of the robot in real-time via Rivz, Rqt, and V-rep. Experiment results demonstrate the advantageous operability and reliability of the system.
AB - Simultaneous localization and mapping (SLAM) constitutes the core challenge in autonomous navigation while avoiding obstacles for mobile robots. Traditional robots require close-range operators during mapping, and remote control remains difficult in a complex environment. Furthermore, the height of sensors limits the detection of small obstacles in 2D mapping. This paper presents a robot system that solves these problems. The system operates SLAM remotely, navigates narrow paths, and estimates the location of small obstacles beyond the detection range of 2D lidar. The experiments utilized the Robot Operating System and an open source GMapping software package. Lidar, a camera, and an inertial measurement sensor unit enabled the remote monitoring of the robot in real-time via Rivz, Rqt, and V-rep. Experiment results demonstrate the advantageous operability and reliability of the system.
KW - GMapping
KW - IMU sensor
KW - Mobile robot
KW - Ros
KW - Simultaneous localization and mapping
UR - http://www.scopus.com/inward/record.url?scp=85072400320&partnerID=8YFLogxK
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U2 - 10.1109/ICMA.2019.8816250
DO - 10.1109/ICMA.2019.8816250
M3 - Conference contribution
AN - SCOPUS:85072400320
T3 - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
SP - 174
EP - 179
BT - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Mechatronics and Automation, ICMA 2019
Y2 - 4 August 2019 through 7 August 2019
ER -