A self-organized shape formation in swarm robots

Abstract

This work proposes a functional method-based approach for shape formation. The core principle in swarm intelligence is that simple swarm behaviour can be established with assigning the rules. To keep all the agents in the given shape and to build the set of motion, desired locations must be assigned to govern the leader and the other followers. Given the restrictions of communication, collision avoidance, and computation challenges, the proposed work is ideal for swarm robots shape formation. The proposed dynamic shape formation uses the shortest path method and the obstacle avoidance algorithm. Natural swarm inspired method based on the Particle Swarm Optimization (PSO) model is used to form the robots in the assigned position. A set of simulation analysis demonstrate that the convergence and scalability of our proposed technique. The effectiveness of pattern formation is increased further by adjusting specific parameters in the PSO model with the aid of the MATLAB simulator.