Collective Robotics Search using Particle System


Abstract – This work introduces the implementation of particle system to besimulated to work as a group of unmanned mobile robots (swarm robots). These robotsare able to locate a specified target in the predefined environment with high efficiencywhen driven by an optimized Particle Swarm Optimization (PSO) algorithm. Theapplication of the particle system to the mobile robots to search for a target in theenvironment is called Collective Robotics Search (CRS) problem. The main benefit ofthis application is to evolve better solutions than using single robot through thecollective interaction of all robots between them to achieve the searching tasksuccessfully. Particle system has been chosen in this work to employ the mobile robotsin the CRS problem due to its simplicity and easy to implement. To measure theperformance of this simulation, a simple obstacle free environment will be used toimplement behaviors of the group of mobile robots when those robots are used to searchfor a single target. The results of this work show that applying PSO to a CRS problemin off-line and on-line approaches are efficient in terms of minimum error and alsominimum number of iterations during the evolutionary process.