On self-organised aggregation dynamics in swarms of robots with informed robots

Abstract

Aggregation is a process observed in natural systems whereby individuals gather together to form large cluster. Recent studies with cockroaches and robots have shown that relatively simple individual mechanisms can account for how individuals manage to gather on a single shelter when two or more are available in the environment. In this paper, we use simulated swarms of robots to further explore the aggregation dynamics generated by these simple individual mechanisms. Our objective is to study the introduction of "informed robots", and to study how many of these are needed to direct the aggregation process toward a pre-defined site among those available in the environment. Informed robots are members of a group that selectively avoid the site/s where no aggregate should emerge, and stop only on the experimenter predefined site/s for aggregation. We study the aggregation process with informed robots in three different scenarios: two that are morphologically symmetric, whereby the different types of aggregation site are equally represented in the environment; and an asymmetric scenario, whereby the target site has an area that is half the area of the sites that should be avoided. We first show what happens when no robot in the swarm is informed: in symmetric environments, the swarm is able to break the symmetry and aggregates on one of the two 1

Swarm Robotics: A Perspective on the Latest Reviewed Concepts and Applications

“…Aiming to demonstrate the aggregation dynamics, Firat et al [ 95 ] concentrate the investigation on the self-organized aggregation of swarm-robot systems. According to the authors, the goal was to survey the prelude of “informed robots” and examine the amount of these agents are required to conduct the aggregation development regarding a predetermined area among those accessible in ambiance.…”

Is order creation through disorder in additive manufacturing possible?

“…Reconfigurable cellular robotics (La boîte verte. Des recherches de forme pour des essaims robotiques collaboratifs, 2020; Fiévet, 2004;Firat et al, 2020;Goldstein et al, 2005;Hornyak, 2019;Jin & Meng, 2012;Mathews et al, 2017). Competitive behaviour is the opposite of cooperative behaviour.…”

“…For synergistics, this is mathematically translated by the variation of the order (or control) parameters of the system by the environment. The system thus sees its stability disturbed, which can lead to other motives, other regularities and, consequently, to the achievement of desired objectives (Firat et al, 2020). The creation of transformative novelty is thus possible because of this break in the logical sequence by bifurcating between a set of interacting elements (Schwarz, 1977).…”

Constructing a cohesive pattern for collective navigation based on a swarm of robotics

“…In the probabilistic method, every robot has a random component and is adapted in the robot's interaction approach with the environment (Khaldi et al, 2019). Besides, probabilistic methods are inspired by nature, like cockroaches and bees (Firat et al, 2020;Valentini, Ferrante & Dorigo, 2017). The artificial evolution method is based on the concept of adaptation.…”