Robust Estimation of Camera Rotation, Translation and Focal Length at High Outlier Rates
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Distributed, Physics-Based Control of Swarms of Vehicles
Autonomous Robots
Particle swarms and population diversity
Soft Computing - A Fusion of Foundations, Methodologies and Applications
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
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In recent years many investigations have shown that Particle Swarm Optimization(PSO) is a very competitive global optimization heuristic. However, in very complex state spaces the classical PSO algorithm converges too fast and hence provides only suboptimal results. Looking at swarm robotics it seems natural to adopt a repulsive force to avoid this undesired behavior as suggested in Charged PSO but the downside of this is the problem of final convergence in static applications.The contribution of this paper is to introduce a dynamic charge reductionover time defining particle groups which are iteratively merged, reducing the number of charged particles during the optimization run.A visualization of this process shows spontaneous formation of independent particle groups, redolent very much of swarm movement in nature. Optimization results are superior compared to other PSO approaches especially in very complex high dimensional search spaces.