Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence
The nature inspired Swarm Intelligence has laid the foundation for many eclectic applications. This work considers a solution to one such application of Search and Rescue operation, based on Cohort Intelligence (CI) methodology which aims at modelling the behaviour of candidates based on the interac...
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doaj-dd9628e09efd43ff9a4786301935d4212021-10-05T04:21:17ZengElsevierSoft Computing Letters2666-22212020-08-012100006Application of Swarm Robotic System in a Dynamic Environment using Cohort IntelligencePriya Bannur0Purvi Gujarathi1Karthik Jain2Anand J Kulkarni3School of Computer Engineering & Technology, MIT World Peace University, Pune, 411 038, India; Corresponding author.School of Computer Engineering & Technology, MIT World Peace University, Pune, 411 038, IndiaSchool of Computer Engineering & Technology, MIT World Peace University, Pune, 411 038, IndiaSymbiosis Center for Research and Innovation, Symbiosis International (Deemed University), Pune, 412 115, IndiaThe nature inspired Swarm Intelligence has laid the foundation for many eclectic applications. This work considers a solution to one such application of Search and Rescue operation, based on Cohort Intelligence (CI) methodology which aims at modelling the behaviour of candidates based on the interaction amongst each other to achieve a common goal. Every candidate improves its own behaviour by observing all other candidates in the cohort. This method results in the refinement of the performance of the entire system. The research done so far in this application using CI is associated with robots deployed in a static alien establishment. However, this assumption is not suitable in real-life scenarios. In this paper, the obstacle avoidance and path planning of a swarm of robots was implemented while considering a dynamic alien establishment. The problem of robots occasionally getting stuck in the non-convex obstacles has also been solved using a perturbation technique. The following test cases were implemented - No Obstacle Case (NOC), Stationary Obstacles Case (SOC), Single Dynamic Obstacle Case (SDOC), Multiple Dynamic Obstacles Case with Same Velocity (MDOC-SV) and Multiple Dynamic Obstacles Case with Different Velocities (MDOC-DV).http://www.sciencedirect.com/science/article/pii/S2666222120300058Cohort IntelligenceSearch and RescueSwarm RoboticsMetaheuristicsArtificial Intelligence |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Priya Bannur Purvi Gujarathi Karthik Jain Anand J Kulkarni |
spellingShingle |
Priya Bannur Purvi Gujarathi Karthik Jain Anand J Kulkarni Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence Soft Computing Letters Cohort Intelligence Search and Rescue Swarm Robotics Metaheuristics Artificial Intelligence |
author_facet |
Priya Bannur Purvi Gujarathi Karthik Jain Anand J Kulkarni |
author_sort |
Priya Bannur |
title |
Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence |
title_short |
Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence |
title_full |
Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence |
title_fullStr |
Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence |
title_full_unstemmed |
Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence |
title_sort |
application of swarm robotic system in a dynamic environment using cohort intelligence |
publisher |
Elsevier |
series |
Soft Computing Letters |
issn |
2666-2221 |
publishDate |
2020-08-01 |
description |
The nature inspired Swarm Intelligence has laid the foundation for many eclectic applications. This work considers a solution to one such application of Search and Rescue operation, based on Cohort Intelligence (CI) methodology which aims at modelling the behaviour of candidates based on the interaction amongst each other to achieve a common goal. Every candidate improves its own behaviour by observing all other candidates in the cohort. This method results in the refinement of the performance of the entire system. The research done so far in this application using CI is associated with robots deployed in a static alien establishment. However, this assumption is not suitable in real-life scenarios. In this paper, the obstacle avoidance and path planning of a swarm of robots was implemented while considering a dynamic alien establishment. The problem of robots occasionally getting stuck in the non-convex obstacles has also been solved using a perturbation technique. The following test cases were implemented - No Obstacle Case (NOC), Stationary Obstacles Case (SOC), Single Dynamic Obstacle Case (SDOC), Multiple Dynamic Obstacles Case with Same Velocity (MDOC-SV) and Multiple Dynamic Obstacles Case with Different Velocities (MDOC-DV). |
topic |
Cohort Intelligence Search and Rescue Swarm Robotics Metaheuristics Artificial Intelligence |
url |
http://www.sciencedirect.com/science/article/pii/S2666222120300058 |
work_keys_str_mv |
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