Coordination and behavior integration in cooperating simulated robots.

This paper shows how a group of evolved physically-linked robots are able to display a variety of highly coordinated basic behaviours (coordinated motion coordinated obstacle avoidance, coordinated light approaching) and to integrate such behaviours into a single coherent behaviour. In this way the group is capable of searching and approaching a light target in an environment scattered with obstacles, furrows, and holes and of dynamically changing its shape in order to pass through narrow passages. The paper analyses in detail the emerged basic behaviours and shows how the coordination of the group relies upon robust self-organising principles based on a traction sensor that allows the single robots to perceive the "average" direction of motion of the rest of the group

Evolution of collective behaviour in a team of physically linked robots

In this paper we address the problem of how a group of four assembled simulated robots forming a linear structure can co-ordinate and move as straight and as fast as possible. This problem is solved in a rather simple and effective way by providing the robots with a sensor that detects the direction and intensity of the traction that the turret exerts on the chassis of each robot and by evolving their neural controllers. We also show how the evolved robots are able to generalize their ability in rather different circumstance by: (a) producing coordinated movements in teams with varying size, topology, and type of links; (b) displaying individual or collective obstacle avoidance behaviors when placed in an environment with obstacles; (c) displaying object pushing/pulling behavior when connected to or around a given object

Path Planning of Mobile Agents using AI Technique

In this paper, we study coordinated motion in a swarm robotic system, called a swarm-bot. A swarm-bot is a self-assembling and self-organizing. Artifact composed of a swarm of s-bots, mobile robots with the ability to connect to and is connect from each other. The swarm-bot concept is particularly suited for tasks that require all-terrain navigation abilities, such as space exploration or rescue in collapsed buildings. As a first step toward the development of more complex control strategies, we investigate the case in which a swarm-bot has to explore an arena while avoiding falling into holes. In such a scenario, individual s-bots have sensory–motor limitations that prevent them navigating efficiently. These limitations can be overcome if the s-bots are made to cooperate. In particular, we exploit the s-bots’ ability to physically connect to each other. In order to synthesize the s-bots’ controller, we rely on artificial evolution, which we show to be a powerful tool for the production of simple and effective solutions to the hole avoidance task

Evolutionary swarm robotics: a theoretical and methodological itinerary from individual neuro-controllers to collective behaviours

In the last decade, swarm robotics gathered much attention in the research community. By drawing inspiration from social insects and other self-organizing systems, it focuses on large robot groups featuring distributed control, adaptation, high robustness, and flexibility. Various reasons lay behind this interest in similar multi-robot systems. Above all, inspiration comes from the observation of social activities, which are based on concepts like division of labor, cooperation, and communication. If societies are organized in such a way in order to be more efficient, then robotic groups also could benefit from similar paradigms

Swarm intelligence and its applications in swarm robotics

This work gives an overview of the broad field of computational swarm intelligence and its applications in swarm robotics. Computational swarm intelligence is modelled on the social behavior of animals and its principle application is as an optimization technique. Swarm robotics is a relatively new and rapidly developing field which draws inspiration from swarm intelligence. It is an interesting alternative to classical approaches to robotics because of some properties of problem solving present in social insects, which is flexible, robust, decentralized and self-organized. This work highlights the possibilities for further research

Physical connections and cooperation in swarm robotics

We describe a new multi-robot system, named SWARM-BOTS, that exploits physical inter-connections to solve tasks that are impossible for a single robot. This is for instance the case of passing large gaps or high steps in all-terrain conditions. In order to achieve this type of autonomous collective operations, the design of the type of connection, as well as its sensors and actuators, plays a key role. This paper presents the choices made in the SWARM-BOTS project and the know-how collected until now. The requirements for autonomous operation and mobility of each robots have led to the development of a connectivity very different those found in selfrecon gurable robots. Some of the solutions employed for this problem are inspired upon physical connectivity of social insects. We also illustrate with two experiments how sensors and actuators allow autonomous operation in connection, release as well as passive and active exploitation of inter-robot degrees of freedom (DOF)