BACTERIA COLONY APPROACHES WITH VARIABLE VELOCITY APPLIED TO PATH OPTIMIZATION OF MOBILE ROBOTS

Abstract

During the course of evolution, colonies of ants, bees, wasps, bacteria and termites have developed sophisticated behavior, intricate communication capabilities, decentralized colony control, group foraging strategies and a high degree of worker cooperation when tackling tasks. Utilizing these capabilities, any bio-inspired optimization techniques using analogy of swarming principles and social behavior in nature  swarm intelligence  have been adopted to solve a variety of engineering and mobile robotics problems.In this paper, new approaches of bacteria colony optimization method with variable velocity based on uniform, Gauss and Cauchy distributions were tested. Bacteria colony, a swarm intelligence methodology, is evaluated for a path planning problem in static environment of mobile robotics. The simulation results are compared with classical bacteria colony approach and genetic algorithms.