Title :
Modified particle swarm optimization for odor source localization of multi-robot
Author :
Gong, Dun-Wei ; Qi, Cheng-liang ; Zhang, Yong ; Li, Ming
Author_Institution :
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
Abstract :
Odor source localization is very important in real world applications. We studied the problem of odor source localization and presented a modified particle swarm optimization algorithm for odor source localization of multi robot. The algorithm dynamically adjusts two learning factors in the velocity update equation based on the effect of wind on self cognition and social cognition of a particle. In addition, an artificial potential field method is employed to improve the performance of our algorithm. We conducted various experiments in time-varying environments, and the experimental results confirm the superiority of our algorithm.
Keywords :
electronic noses; learning (artificial intelligence); multi-robot systems; particle swarm optimisation; artificial potential field method; learning factors; modified particle swarm optimization; multirobot system; odor source localization; self-cognition; social cognition; velocity update equation; wind effect; Algorithm design and analysis; Convergence; Educational institutions; Heuristic algorithms; Particle swarm optimization; Robots; Strontium; anemotaxis; multi-robot; odor source localization; particle swarm optimization;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949609
