Population Density Particle Swarm Optimized Improved Multi-robot Cooperative Localization Algorithm
نویسندگان
چکیده
In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environment and particle swarm, through dynamic adjustment of particle swarm densities based on Lotka-Volterra competition equations, PDPSO-PF improves particle diversities, speeds up the evolution of the algorithm and enhances the effectiveness of prediction for multi-robot positioning. Studies show that PDPSO-PF improves both the convergence speed and accuracy, thus is suitable for multi-robot cooperative positioning.
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