A new multi-robot search algorithm using Probabilistic Finite State Machine and Lennard-Jones potential function
Lists
Lists
Khan, Muhammad S. A., HASAN, Mohammad and Ahmed, Tarem (2018) A new multi-robot search algorithm using Probabilistic Finite State Machine and Lennard-Jones potential function. In: the IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2018), 12-15 Dec 2018, Malaysia. (Submitted)
|
Text
ROBIO 2018 Paper 241.pdf - AUTHOR'S ACCEPTED Version (default) Available under License All Rights Reserved. Download (297kB) | Preview |
Abstract or description
Swarm robotics is a decentralized approach to
robotic systems. This paper investigates the problem of search
and rescue using swarm robots. A multi-robot search algorithm
using probabilistic finite state machine and interaction inspired
by Lennard-Jones potential function has been proposed.
Probabilistic finite state machine has been used 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 result is promising. Algorithmic
complexity comparison with Robotic Darwinian Particle Swarm
Optimization and Glowworm Swam Optimization appear
favourable.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Faculty: | School of Computing and Digital Technologies > Computing |
| Event Title: | the IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2018) |
| Event Location: | Malaysia |
| Event Dates: | 12-15 Dec 2018 |
| Depositing User: | Mohammad HASAN |
| Date Deposited: | 19 Dec 2018 14:47 |
| Last Modified: | 24 Feb 2023 13:53 |
| Related URLs: | |
| URI: | https://eprints.staffs.ac.uk/id/eprint/5028 |
Actions (login required)
 |
View Item |
