WiFi based communication and localization of an autonomous mobile robot for refinery inspection

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.

[1]  John Krumm,et al.  Accuracy characterization for metropolitan-scale Wi-Fi localization , 2005, MobiSys '05.

[2]  Y. Ebihara.  Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[3]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[4]  A. Aggarwal.  The art gallery theorem: its variations, applications and algorithmic aspects , 1984 .

[5]  G. Ros,et al.  Visual SLAM for Driverless Cars : A Brief Survey , 2012 .

[6]  Birgit GRAF,et al.  Mobile Robotics for Offshore Automation , 2007 .

[7]  Khaled Al-Wahedi,et al.  Development of an Oil and Gas Refinery Inspection Robot , 2014 .

[8]  Philip A. Whiting,et al.  Autonomous RF Surveying Robot for Indoor Localization and Tracking , 2011 .

[9]  Wei Wang,et al.  List-coloring based channel allocation for open-spectrum wireless networks , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

[10]  Alexander Verl,et al.  Mobile robots for offshore inspection and manipulation , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Himanshu Gupta,et al.  Connected sensor cover: self-organization of sensor networks for efficient query execution , 2003, IEEE/ACM Transactions on Networking.

[12]  Paolo Toth,et al.  A survey on vertex coloring problems , 2010, Int. Trans. Oper. Res..

[13]  Rekha Jain,et al.  Wireless Sensor Network -A Survey , 2013 .

[14]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[15]  Alex Talevski,et al.  Applications of Wireless Sensor Networks in the Oil, Gas and Resources Industries , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[16]  Himanshu Gupta,et al.  Connected K-coverage problem in sensor networks , 2004, Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969).

[17]  Sergios Theodoridis,et al.  A Novel Efficient Cluster-Based MLSE Equalizer for Satellite Communication Channels with-QAM Signaling , 2006, EURASIP J. Adv. Signal Process..

[18]  François Marx,et al.  Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning , 2006, EURASIP J. Adv. Signal Process..

[19]  Ashish Raniwala,et al.  Deployment Issues in Enterprise Wireless LANs , 2003 .

[20]  Kris Vanhecke,et al.  Coverage prediction and optimization algorithms for indoor environments , 2012, EURASIP J. Wirel. Commun. Netw..

[21]  Katia Jaffrès-Runser,et al.  On predicting in-building WiFi coverage with a fast discrete approach , 2007 .

[22]  Jim Kurose,et al.  Computer Networking: A Top-Down Approach , 1999 .