In this paper, we present a comprehensive study on autonomous self-assembly. In particular, we discuss the self-assembling capabilities of the swarm-bot, a distributed robotics concept that lies at the intersection between collective and selfreconfigurable robotics. A swarm-bot comprises autonomous mobile robots called s-bots. S-bots can either act independently or self-assemble into a swarm-bot by using their grippers. We report on

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.

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-organising artifact, composed of a swarm of s-bots, mobile robots with the ability to connect to and disconnect 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 another. In order to synthesise 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.

Distributed coordination of groups of individuals accomplishing a common task without leaders, with little communication, and on the basis of selforganising principles, is an important research issue within the study of collective behaviour of animals, humans and robots. The paper shows how distributed coordination allows a group of evolved physicallylinked simulated robots (inspired by a robot under construction) to display a variety of highly coordinated basic behaviours such as collective motion, collective obstacle avoidance, and collective light approaching, and to integrate them in a coherent fashion. In this way the group is capable of searching and approaching a light target in an environment scattered with obstacles, furrows, and holes, where robots acting individually fail. The paper shows how the emerged coordination of the group relies upon robust self-organising principles (e.g. positive feedback) based on a special sensor that allows the single robots to perceive the “average ” group’s motion direction. The paper also presents a robust solution to a difficult coordination problem, that might also be encountered by some organisms, caused by the fact that the robots have to be capable of moving in any direction while being physically connected. Finally, the paper shows how the evolved distributed coordination mechanisms scale very well with respect to the number of robots, the way in which robots are assembled, the structure of the environment, and several other aspects. 1.

This paper provides an overview of the SWARM-BOTS project, a robotics project sponsored by the Future and Emerging Technologies program of the European Commission (IST-2000-31010). We describe the s-bot, asmallautonomous robot with self-assembling capabilities that we designed and built within the project. Then we illustrate the cooperative object transport scenario that we chose to use as a test-bed for our robots. Last, we report on results of experiments in which a group of s-bots perform a variety of tasks within the scenario which may require selfassembling, physical cooperation and coordination. 1.

Abstract. This paper provides an overview of the SWARM-BOTS project, a robotic project sponsored by the Future and Emerging Technologies program of the European Community (IST-2000-31010). The paper illustrates the robot hardware, and the results of experimental works in which distributed adaptive controllers are designed to allow the agents to perform a variety of tasks which require cooperation and coordination among the members of a group. 1

In this study, a systematic analysis of probabilistic aggregation strategies in swarm robotic systems is presented. A generic aggregation behavior is proposed as a combination of four basic behaviors: obstacle avoidance, approach, repel,andwait. The latter three basic behaviors are combined using a three-state finite state machine with two probabilistic transitions among them. Two different metrics were used to compare performance of strategies. Through systematic experiments, how the aggregation performance, as measured by these two metrics, change 1) with transition probabilities, 2) with number of simulation steps, and 3) with arena size, is studied. 1.

From an engineering point of view, the problem of coordinating a set of autonomous, mobile robots for the purpose of cooperatively performing a task has been studied extensively over the past decade. In contrast, in this paper we aim at an understanding of the fundamental algorithmic limitations on what a set of autonomous mobile robots can or cannot achieve. We therefore study a hard task for a set of weak robots. The task is for the robots in the plane to form any arbitrary pattern that is given in advance. This task is fundamental in the sense that if the robots can form any pattern, they can agree on their respective roles in a subsequent, coordinated action. The robots are weak in several aspects. They are anonymous; they cannot explicitly communicate with each other, but only observe the positions of the others; they cannot remember the past; they operate in a very strong form of asynchronicity. We show that the tasks that such a system of robots can perform depend strongly on their common agreement about their environment, i.e., the readings of their environment sensors. If the robots have no common agreement about their environment, they cannot form an arbitrary pattern. If each robot has a compass needle that indicates North (the robot world is a flat surface, and compass needles are parallel), then any odd number of robots can form an arbitrary pattern, but an even number cannot (in the worst case). If each robot has two independent compass needles, say North and East, then any set of robots can form any pattern.

When one attempts to use artificial evolution to develop behaviors for a swarm robotic system, he is faced with decisions to be made regarding the parameters of the evolution. In this paper, we chose the aggregation behavior as a case, and systematically studied the performance and the scalability of aggregation behaviors of perceptron controllers evolved for a simulated swarm robotic system with different parameter settings. We have conducted four experiments, varying some of the parameters and derived rules of thumb which can be of guidance to the use of evolutionary methods to generate other swarm robotic behaviors. 1.

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