Robot Swarm Flocking on a 2D Triangular Graph

Cheraghi, Ahmad Reza; Janete, Asma Ben; Graffi, Kálmán

doi:10.1109/acirs49895.2020.9162599

Cited by 6 publications

(5 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some controllers do not apply these three rules to all nearby agents. There are algorithms (Fetecau, 2011; Yasuda et al, 2014; Cheraghi et al, 2020) using the three successive detection zones from the controller of Couzin et al’s. (2002) work.…”

Section: Self-organisation Methodsmentioning

confidence: 99%

“…Attraction, alignment and repulsion (Reynolds, 1987) ( Reynolds, 1987;Fetecau, 2011;Yasuda et al, 2014;Cheraghi et al, 2020;Couzin et al, 2002;Aoki, 1982;Wilensky, 1998;Moeslinger et al, 2009;Leonard & Fiorelli, 2001;Fierro et al, 2001;Ferrante et al, 2012;Bonnefond et al, 2021;Stranieri et al, 2011;Hahn et al, 2019;Wood & Ackland, 2007;Vásárhelyi et al, 2018;Ramos et al, 2019;Hoang et al, 2021) (Mathews et al, 2012) (Couzin et al, 2002) Preservation of connectivity (Khaldi et al, 2018(Khaldi et al, , 2020Berlinger et al, 2021) (Tanner et al, 2003a(Tanner et al, , 2003b(Tanner et al, , 2007Olfati-Saber, 2006;Zavlanos et al, 2007;McCook & Esposito, 2007;Su et al, 2009;Wen et al, 2012;Ning et al, 2017;Dai et al, 2019;Gu & Hu, 2008;Yu et al, 2010) (McLurkin & Smith, 2004De Silva et al, 2005;Ugur et al, 2007;…”

Section: Self-organisation Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A unifying method-based classification of robot swarm spatial self-organisation behaviours

et al. 2023

View full text Add to dashboard Cite

Self-organisation in robot swarms can produce collective behaviours, particularly through spatial self-organisation. For example, it can be used to ensure that the robots in a swarm move collectively. However, from a designer’s point of view, understanding precisely what happens in a swarm that allows these behaviours to emerge at the macroscopic level remains a difficult task. The same behaviour can come from multiple different controllers (ie the control algorithm of a robot) and a single controller can give rise to multiple different behaviours, sometimes caused by slight changes in self-organisation. To grasp the causes of these differences, it is necessary to investigate the relationships between the many methods of self-organisation that exist and the various behaviours that can be obtained. The work presented here addresses self-organisation in robot swarms by focusing on the main behaviours that lead to spatial self-organisation of the robots. First, we propose a unified definition of the different behaviours and present an original classification system highlighting ten self-organisation methods that each allow one or more behaviours to be performed. An analysis, based on this classification system, links the identified mechanisms with behaviours that could be considered as obtainable or not. Finally, we discuss some perspectives on this work, notably from the point of view of an operator or designer.

show abstract

Section: Self-organisation Methodsmentioning

confidence: 99%

Section: Self-organisation Methodsmentioning

confidence: 99%

A unifying method-based classification of robot swarm spatial self-organisation behaviours

et al. 2023

View full text Add to dashboard Cite

show abstract

“…There is some research published with the simulator Swarm-Sim. Such as coating an object with help of swarm [89], [90], the flocking movement of swarms in a triangular graph [91], a simulation of marking any given field with obstacle, and three more [92], [93], [94]. SCRIMMAGE: Simulating Collaborative Robots in Massive Multi-Agent Game Execution (SCRIMMAGE) [95] is a 3-dimensional, open-source simulation environment for the testing and comparing of mobile robotics algorithms and behaviors.…”

Section: Swarmanoidmentioning

confidence: 99%

Past, Present, and Future of Swarm Robotics

Cheraghi¹,

Shahzad²,

Graffi³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Swarm Robotics is an emerging field of adapting the phenomenon of natural swarms to robotics. It is a study of robots that are aimed to mimic natural swarms, like ants and birds, to form a system that is scalable, flexible, and robust. These robots show self-organization, autonomy, cooperation, and coordination amongst themselves. The cost and design complexity factor is aimed to keep low, hence trying to form systems that are very much similar to natural swarms. The robots operate without any central entity to control them, and the communication amongst the robots can either be direct (robot-to-robot) or indirect (robotto-environment). Swarm robotics has a wide range of application fields, from simple household tasks to military missions. This paper reviews the swarm robotics approach from its history to its future. It discusses the basic idea of swarm robotics, its important features, simulators, projects, real life applications and some future ideas.

show abstract

“…One of the main components of a swarming system is the exhibition of cooperative behavior. A flock involves multiple agents that possess real-time group behavior capabilities that facilitate achieving a common target, such as foraging or migration [4,5]. The design of swarm robotics systems is guided by swarm intelligence principles.…”

Section: Introductionmentioning

confidence: 99%

“…A controller is an essential structure that is used in the implementation and simulation of swarm systems [15]. There are three main approaches to formation control systems [4,12,16]: the leader-follower approach [12,[17][18][19], the virtual structure approach [1,20,21], and the behavior-based approach [5,14,16,[22][23][24][25][26]. Despite the simplicity of the leader-follower approach, it may suffer from being highly dependent on the leader agent and from the large amount of information exchange required between the leader and each of the followers due to being a centralized system [4].…”

Section: Introductionmentioning

confidence: 99%

Effect of Formation Size on Flocking Formation Performance for the Goal Reach Problem

et al. 2022

View full text Add to dashboard Cite

Flocking is one of the swarm tasks inspired by animal behavior. A flock involves multiple agents aiming to achieve a goal while maintaining certain characteristics of their formation. In nature, flocks vary in size. Although several studies have focused on the flock controller itself, less research has focused on how the flock size affects flock formation and performance. In this study, we address this problem and develop a simple flock controller for goal-zone-reaching tasks. The developed controller is intended for a two-dimensional environment and can handle obstacles as well as integrate an additional invented feature, called sensing power, in order to simulate the natural dynamics of migratory birds. This controller is simulated using the NetLogo simulation tool. Several experiments were conducted with and without obstacles, accompanied by changes in the flock size. The simulation results demonstrate that the flock controller is able to successfully deliver the flock to the goal zone. In addition, changes in the flock size affect multiple metrics, such as the time required to reach the goal (and, consequently, the time required to complete the flocking task), as well as the number of collisions that occur.

show abstract

Robot Swarm Flocking on a 2D Triangular Graph

Cited by 6 publications

References 12 publications

A unifying method-based classification of robot swarm spatial self-organisation behaviours

A unifying method-based classification of robot swarm spatial self-organisation behaviours

Past, Present, and Future of Swarm Robotics

Effect of Formation Size on Flocking Formation Performance for the Goal Reach Problem

Contact Info

Product

Resources

About