Foraging Behaviors – Pheromone, Task Allocation, and Trophallaxis -A Relative Comparison for Robotic Swarm Foraging
Authors: Ralph Nicole R.Barcos, Angelo R. Dela Cruz, Edison A. Roxas, Argel A. Bandala, Laurence Gan Lim, Elmer P. Dadios and Ryan Rhay P. Vicerra
Abstract
A group of algorithm enhancing collective behavior is inspired by the animals working together as a group such as ants, bees, and etc. In connection, swarm is defined as a set of two or more independent homogenous or heterogeneous agents acting upon a common environment in a coherent fashion which generates emergent behavior. The development of artificial swarms or robotic swarms has attracted a lot of researchers in the last two decades including pheromone, trophallaxis and task allocation algorithms. However, among these swarm based algorithms, the most efficient in terms of group performance, efficiency and interference in collecting the dusts or objects in an environment with variable terrains has not been identified. With this, the researchers see the need to developed swarm simulation platform that would compare the swarmbehavior- based algorithms for an ideal use of robots in different environments in dust collection.