A new multi robot search algorithm using probabilistic finite state machine and Lennard Jones potential function
Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
BRAC University
Abstract
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.
Description
Cataloged 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.
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.
Keywords
Autonomous robots, Multi-robot systems, Performance analysis, Search and rescue, Swarm intelligence
