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Optimized Node Deployment Algorithm and Parameter Investigation in a Mobile Sensor Network for Robotic Systems
Author(s) -
Rongxin Tang,
Chengfei Nie,
Xin Qian,
Xiaohua Deng,
Zhe Chen,
ZhiWei Liu,
Meng Zhou,
Ye Pang,
Xiaojun Xu
Publication year - 2015
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/61443
Subject(s) - computer science , software deployment , wireless sensor network , robotics , algorithm , delaunay triangulation , artificial intelligence , node (physics) , topology (electrical circuits) , real time computing , robot , computer network , mathematics , structural engineering , combinatorics , engineering , operating system
Mobile sensor networks are an important part of modern robotics systems and are widely used in robotics applications. Therefore, sensor deployment is a key issue in current robotics systems research. Since it is one of the most popular deployment methods, in recent years the virtual force algorithm has been studied in detail by many scientists. In this paper, we focus on the virtual force algorithm and present a corresponding parameter investigation for mobile sensor deployment. We introduce an optimized virtual force algorithm based on the exchange force, in which a new shielding rule grounded in Delaunay triangulation is adopted. The algorithm employs a new performance metric called ‘pair-correlation diversion', designed to evaluate the uniformity and topology of the sensor distribution. We also discuss the implementation of the algorithm's computation and analyse the influence of experimental parameters on the algorithm. Our results indicate that the area ratio, φs, and the exchange force constant, G, influence the final performance of the sensor deployment in terms of the coverage rate, the convergence time and topology uniformity. Using simulations, we were able to verify the effectiveness of our algorithm and we obtained an optimal region for the (φs, G)-parameter space which, in the future, could be utilized as an aid for experiments in robotic sensor deployment

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