Modelling a wireless connected swarm of mobile robots

Winfield, Alan F.T.; Liu, Wenguo; Nembrini, Julien; Martinoli, Alcherio

Abstract

It is a characteristic of swarm robotics that modelling the overall swarm behaviour in terms of the low-level behaviours of individual robots is very difficult. Yet if swarm robotics is to make the transition from the laboratory to real-world engineering realisation such models would be critical for both overall validation of algorithm correctness and detailed parameter optimisation. We seek models with predictive power: models that allow us to determine the effect of modifying parameters in individual robots on the overall swarm behaviour. This paper presents results from a study to apply the probabilistic modelling approach to a class of wireless connected swarms operating in unbounded environments. The paper proposes a probabilistic finite state machine (PFSM) that describes the network connectivity and overall macroscopic behaviour of the swarm, then develops a novel robot-centric approach to the estimation of the state transition probabilities within the PFSM. Using measured data from simulation the paper then carefully validates the PFSM model step by step, allowing us to assess the accuracy and hence the utility of the model. © Springer Science + Business Media, LLC 2008.

• Journal Article Type: Article
• Publication Date: Sep 15, 2008
• Deposit Date: Feb 19, 2013
• Publicly Available Date: Apr 12, 2016
• Journal: Swarm Intelligence
• Print ISSN: 1935-3812
• Electronic ISSN: 1935-3820
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 2-4
• Pages: 241-266
• DOI: https://doi.org/10.1007/s11721-008-0018-0
• Keywords: swarm robotics, modelling, wireless ad-hoc network
• Public URL: https://uwe-repository.worktribe.com/output/1022794
• Publisher URL: http://dx.doi.org/10.1007/s11721-008-0018-0
• Related Public URLs: http://www.springerlink.com/content/b84624225j253772/
• Additional Information: Additional Information : The original publication is available at www.springerlink.com
• Contract Date: Apr 12, 2016