Hasan, Mohammad S.Ahmed, TaremKhan, Md. Shadnan Azwad2022-06-122022-06-1220172017ID 13321076http://hdl.handle.net/10361/16959Cataloged from PDF version of thesis.Includes bibliographical references (pages 31-33).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.Swarm robotics is a decentralized approach to robotic systems. This paper exammes the problem of search and rescue using swarm robots. We present as solution a multi-robot search algorithm using probabilistic finite state machine and interaction inspired by Lennard-Jones potential function. The approach utilizes a finite state machine to separate the tasks performed and to change coordination rules according to the circumstances and social probabilities. The approach is tested in various scenarios to test flexibility, scalability and robustness. The performance results are promising and comparison with Robotic Darwinian Particle Swarm Optimization and Glowworm Swam Optimization for algorithmic complexity appear favourable.33 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Autonomous robotsMulti-robot systemsPerformance analysisSearch and rescueSwarm intelligenceRobots.Automatic control engineering.Computer algorithms.Swarm intelligence.Thesis