A new multi robot search algorithm using probabilistic finite state machine and Lennard Jones potential function

dc.contributor.advisorHasan, Mohammad S.
dc.contributor.advisorAhmed, Tarem
dc.contributor.authorKhan, Md. Shadnan Azwad
dc.date.accessioned2022-06-12T05:32:17Z
dc.date.available2022-06-12T05:32:17Z
dc.date.issued2017
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 31-33).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
dc.description.abstractSwarm 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.
dc.identifier.otherID 13321076
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/e7312a2b-3854-4fec-be8e-a65181941252
dc.identifier.urihttp://hdl.handle.net/10361/16959
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectAutonomous robots
dc.subjectMulti-robot systems
dc.subjectPerformance analysis
dc.subjectSearch and rescue
dc.subjectSwarm intelligence
dc.titleA new multi robot search algorithm using probabilistic finite state machine and Lennard Jones potential function
dc.typeThesis

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