DocumentCode :
1873866
Title :
A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy
Author :
Dada, Emmanuel Gbenga ; Ramlan, Effirul Ikhwan
Author_Institution :
Dept. of Artificial Intell., Univ. of Malaya, Kuala Lumpur, Malaysia
fYear :
2015
fDate :
21-23 April 2015
Firstpage :
93
Lastpage :
98
Abstract :
This paper presents a hybrid algorithm called Primal-Dual-PSO algorithm to address the problem of swarm robotics flocking motion. This algorithm combines the explorative ability of PSO with the exploitative capacity of the Primal Dual Interior Point Method. We hypothesize that the fusion of the two algorithms provides a strong probability of avoiding premature convergence, and also ensure that the robots are not trapped in their local minimal. Our simulation result provides a clear indication of the effectiveness of the algorithm. The hybrid algorithm performs better in terms of precision, rate of convergence, steadiness, robustness and flocking capability for homogenous set of swarm robots.
Keywords :
convergence; motion control; multi-robot systems; particle swarm optimisation; flocking capability; homogenous swarm robot set; hybrid primal-dual-PSO algorithm; premature convergence; primal dual interior point method; swarm robotics flocking motion; swarm robotics flocking strategy; Algorithm design and analysis; Convergence; Heuristic algorithms; Optimization; Real-time systems; Robot kinematics; Interior Point Method; Particle Swarm Optimization (PSO); Primal-Dual; gbest; lbest;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing Technology and Information Management (ICCTIM), 2015 Second International Conference on
Conference_Location :
Johor
Print_ISBN :
978-1-4799-6210-5
Type :
conf
DOI :
10.1109/ICCTIM.2015.7224599
Filename :
7224599
Link To Document :
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