Summary. Multi-robot systems have been studied in tasks that require the robots to be physically linked. In such a configuration, a group of robots may navigate a terrain that proves too difficult for a single robot. On the contrary, many collective tasks can be accomplished more efficiently by a group of independent robots. This paper is about swarm-bot, a robotic system that can operate in both configurations and autonomously switch from one to the other. We examine the performance of a single robot and of groups of robots selfassembling with an object or another robot. We assess the robustness of the system with respect to different types of rough terrain. Finally, we evaluate the performance of swarms of 16 physical robots. At present, for self-assembly in autonomous, mobile robotics, swarm-hots is the state of the art for what concerns reliability, robustness and speed.

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

In this paper, we review half a century of research on the design of systems displaying (physical) self-assembly of macroscopic components. We report on the experience gained in the design of 21 such systems, exhibiting components ranging from passive mechanical parts to mobile robots. We present a taxonomy of the systems and discuss design principles and functions. Finally, we summarize the main achievements and indicate potential directions for future research.

Group transport is performed in many natural systems and has become a canonical task for studying cooperation in robotics. We simulate a system of simple, insect-like robots that can move autonomously and grasp objects as well as each other. We use artificial evolution to produce solitary transport and group transport behaviors. We show that robots, even though not aware of each other, can be effective in group transport. Group transport can even be performed by robots that behave as in solitary transport. Still, robots engaged in group transport can benefit from behaving differently from robots engaged in solitary transport. The best group transport behaviors yielded by half of the evolutions let robots organize into self-assembled structures. This provides evidence that self-assembly can provide adaptive value to individuals that compete in an artificial evolution based on task performance. We conclude the article by discussing potential implications for evolutionary biology and robotics. Keywords group transport · solitary · social behavior · evolution of cooperation · self-assembly · autonomous robots · evolutionary robotics · swarm robotics · swarm intelligence · evolutionary biology 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.

Swarm robotics draws inspiration from decentralized self-organizing biological systems in general and from the collective behavior of social insects in particular. In social insect colonies, many tasks are performed by higher order group or team entities, whose task-solving capacities transcend those of the individual participants. In this paper, we investigate the emergence of such higher order entities. We report on an experimental study in which a team of physical robots performs a foraging task. The robots are “identical ” in hardware and control. They make little use of memory and take actions purely on the basis of local information. Our study advances the current state of the art in swarm robotics with respect to the number of real-world robots engaging in teamwork (up to 12 robots in the most challenging experiment). To the best of our knowledge, in this paper we present the first self-organized system of robots that displays a dynamical hierarchy of teamwork (with cooperation also occurring among higher order entities). Our study shows that teamwork requires neither individual recognition nor differences between individuals. This result might also contribute to the ongoing debate on the role of these characteristics in the division of labor in social insects.

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Abstract — Mobile robots are said to be capable of selfassembly when they can autonomously form physical connections with each other. Despite the recent proliferation of selfassembling systems, little work has been done on using selfassembly to add functional value to a robotic system, and even less on quantifying the contribution of self-assembly to system performance. In this study we demonstrate and quantify the performance benefits of i) acting as a physically larger self-assembled entity, ii) using self-assembly adaptively and iii) making the robots morphologically aware (the self-assembled robots leverage their new connected morphology in a task specific way). In our experiments, two real robots must navigate to a target over a-priori unknown terrain. In some cases the terrain can only be overcome by a self-assembled connected entity. In other cases, the robots can reach the target faster by navigating individually. I.

Abstract — We study a simple algorithm inspired by the Brazil nut effect for achieving segregation in a swarm of mobile robots. The algorithm lets each robot mimic a particle of a certain size and broadcast this information locally. The motion of each particle is controlled by three reactive behaviors: random walk, taxis, and repulsion by other particles. The segregation task requires the swarm to self-organize into a spatial arrangement in which the robots are ranked by particle size (e.g., annular structures or stripes). Using a physics-based computer simulation, we study the segregation performance of swarms of 50 mobile robots. The robots represent particles of three different sizes. We first analyze the problem of how to combine the basic behaviors so as to minimize the percentage of errors in rank. We then show that the system is very robust to noise on inter-robot perception and communication. For a noise level of 50%, the mean percentage of errors in rank is 1%. Moreover, we investigate a simplified version of the control algorithm, which does not rely on communication. Finally, we show that the mean percentage of errors in rank decreases exponentially as the particles ’ size ratio increases. As the error is bounded, one can achieve 100 % error-free segregation. The reduction in error, however, comes at the expense of an increase in the required sensing/communication range. Index Terms—Annulus, Brazil nut effect, center-periphery, muesli effect, pattern formation, robots, segregation, sorting, stripes, swarm intelligence I.