TY - GEN
T1 - WiFi based communication and localization of an autonomous mobile robot for refinery inspection
AU - Sweatt, Marshall
AU - Ayoade, Adewole
AU - Han, Qi
AU - Steele, John
AU - Al-Wahedi, Khaled
AU - Karki, Hamad
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/29
Y1 - 2015/6/29
N2 - Oil and gas refineries can be a dangerous environment for numerous reasons, including heat, toxic gasses, and unexpected catastrophic failures. In order to augment how human operators interact with this environment, a mobile robotic platform is developed. This paper focuses on the use of WiFi for communicating with and localizing the robot. More specifically, algorithms are developed and tested to minimize the total number of WiFi access points (APs) and their locations in any given environment while taking into consideration the throughput requirements and the need to ensure every location in the region can reach at least k APs. When multiple WiFi APs are close together, there is a potential for interference. A graph-coloring heuristic is used to determine AP channel allocation. In addition, WiFi fingerprinting based localization is developed. All the algorithms implemented are tested in real world scenarios with the robot developed and results are promising.
AB - Oil and gas refineries can be a dangerous environment for numerous reasons, including heat, toxic gasses, and unexpected catastrophic failures. In order to augment how human operators interact with this environment, a mobile robotic platform is developed. This paper focuses on the use of WiFi for communicating with and localizing the robot. More specifically, algorithms are developed and tested to minimize the total number of WiFi access points (APs) and their locations in any given environment while taking into consideration the throughput requirements and the need to ensure every location in the region can reach at least k APs. When multiple WiFi APs are close together, there is a potential for interference. A graph-coloring heuristic is used to determine AP channel allocation. In addition, WiFi fingerprinting based localization is developed. All the algorithms implemented are tested in real world scenarios with the robot developed and results are promising.
UR - http://www.scopus.com/inward/record.url?scp=84938225481&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2015.7139821
DO - 10.1109/ICRA.2015.7139821
M3 - Conference contribution
AN - SCOPUS:84938225481
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 4490
EP - 4495
BT - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Y2 - 26 May 2015 through 30 May 2015
ER -