Study of Cooperative Control System for Multiple Mobile Robots Using Particle Swarm Optimization
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Institusion
Universitas Merdeka Malang
Author
Prasetya, Dwi Arman
Subject
Q Science (General)
Datestamp
2020-02-18 03:56:28
Abstract :
The idea of using multiple mobile robots for tracking targets in an unknown environment can be realized with Particle Swarm Optimization proposed by Kennedy and Eberhart in 1995. The actual implementation of an efficient algorithm like Particle Swarm Optimization (PSO) is required when robots need to avoid the randomly placed obstacles in unknown environment and reach the target point. However, ordinary methods of obstacle avoidance have not proven good results in route planning. PSO is a self-adaptive population-based method in which behavior of the swarm is iteratively generated from the combination of social and cognitive behaviors and is an effective technique for collective robotic search problem. When PSO is used for exploration, this algorithm enables robots to travel on trajectories that lead to total swarm convergence on some target.
The idea of using multiple mobile robots for tracking targets in an unknown environment can be realized with Particle Swarm Optimization proposed by Kennedy and Eberhart in 1995. The actual implementation of an efficient algorithm like Particle Swarm Optimization (PSO) is required when robots need to avoid the randomly placed obstacles in unknown environment and reach the target point. However, ordinary methods of obstacle avoidance have not proven good results in route planning. PSO is a self-adaptive population-based method in which behavior of the swarm is iteratively generated from the combination of social and cognitive behaviors and is an effective technique for collective robotic search problem. When PSO is used for exploration, this algorithm enables robots to travel on trajectories that lead to total swarm convergence on some target.
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