DocumentCode :
3221744
Title :
Optimal formation of robots by convex hull and particle swarm optimization
Author :
Jun Liu ; Hongbin Ma ; Xuemei Ren ; Mengyin Fu
Author_Institution :
Sch. of Autom., Beijing Instn. of Technol., Beijing, China
fYear :
2013
fDate :
16-19 April 2013
Firstpage :
104
Lastpage :
111
Abstract :
Formation control problem has been extensively investigated in the literature of multi-agent systems, robotics, and control, etc. Our previous work mainly concentrated on the theoretic study of line formation with three robots, however, it is hard to handle with the formation problem whose number of robots is strictly larger than 3. In order to effectively overcome this problem, this paper incorporates convex hull and the standard PSO algorithm to design the typical formation of several robots. Firstly, on the basis of convex hull of robots, objective function, corresponding to several constraints, is given by the new convex hull method. Secondly, the standard PSO algorithm is adopted to search for the desired positions of several robots to minimize the objective function and satisfy the formation constraints. To demonstrate the effectiveness of the proposed algorithm, numerical results, regarding the formation of several ships in the realistic ocean, mainly concentrate on triangle formation, diamond formation and regular polygon formation.
Keywords :
mobile robots; multi-robot systems; optimal control; particle swarm optimisation; position control; ships; PSO algorithm; convex hull method; diamond formation; formation constraint; formation control problem; multiagent system; objective function; optimal robot formation; particle swarm optimization; regular polygon formation; robotics; ship formation; triangle formation; Algorithm design and analysis; Linear programming; Performance analysis; Robot kinematics; Shape; Standards; Convex hull; Diamond formation; Equilateral triangle; Optimal formation; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Control and Automation (CICA), 2013 IEEE Symposium on
Conference_Location :
Singapore
Type :
conf
DOI :
10.1109/CICA.2013.6611670
Filename :
6611670
Link To Document :
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