Localizing multiple odor sources in dynamic environment using ranged subgroup PSO with flow of wind based on open dynamic engine library

Abstract

A new algorithm based on modified particle swarm optimization (MPSO) which follows a local gradient of the chemical concentration within a plume and follow direction of the wind velocity is investigated. Moreover, the niche or parallel search characteristic is adopted on MPSO to solve the multi-peak and multi-source problem. When using parallel MPSO, subgroup of robot is introduced then each subgroup can locate the odor source. Unfortunately, there is a possibility that more that one subgroup locates one odor sources. This is inefficient because other subgroups locate other source, then we proposed a ranged subgroup method for coping for that problem, then the searching performance will increase. Then ODE (open dynamics engine) library is used for physical modeling of the robot like friction, balancing moment and others. Finally, the statistical analysis shows that the new approach is technically sounds.