Mobile robot connectivity maintenance based on RF mapping

Author

Ayad, Mouloud ; Zhang, J.J. ; Voyles, Richard ; Mahoor, M.H.

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Denver, Denver, CO, USA

fYear

2013

fDate

3-7 Nov. 2013

Firstpage

3398

Lastpage

3405

Abstract

This paper presents a method for proactive robot communication connectivity maintenance based on electromagnetic field (EMF) recognition and signal strength (SS) gradient estimation for mobile robots. To achieve these goals in an efficient manner, we combine EMF recognition method and gradient descent of SS measurements into a proactive robot motion control algorithm in a way that maintains connectivity among mobile robots in the presence of a radio frequency (RF) obstacle. The EMF recognition method utilizes hidden Markov models (HMMs) for learning EMF environments based on SS measurements. The proposed motion control algorithm uses the EMF recognition and gradient method results to drive the robots towards favorable locations in which robots can communicate. The numerical simulation demonstrates promising EMF recognition, robot motion control results and confirms their abilities in proactive robot motion control for connectivity maintenance.

Keywords

collision avoidance; electric potential; gradient methods; hidden Markov models; maintenance engineering; mobile robots; motion control; EMF recognition; RF mapping; electromagnetic field; gradient estimation; hidden Markov models; mobile robot connectivity maintenance; proactive robot communication connectivity maintenance; proactive robot motion control; radio frequency obstacle; signal strength; Hidden Markov models; Robot kinematics; Training; Trajectory; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on

Conference_Location

Tokyo

ISSN

2153-0858

Type

conf

DOI

10.1109/IROS.2013.6696840

Filename

6696840