We demonstrate a scenario in which a mobile robot, according to a plan, builds a structure that it can then enter. The robot interacts with the construction using local sensing. This synthesis of planning and stigmergy opens the way to new construction techniques using mobile robots.

We introduce enhanced directional self-assembly (EDSA) - a novel mechanism for morphology growth through the creation of directed connections in a self-assembling multirobot system. In our approach, a robot inviting a physical connection actively recruits the best located neighboring robot and guides the recruit to the location on its chassis where the connection is required. The proposed mechanism relies on local, high-speed communication between connection inviting robots and their recruits. Communication is based on a hybrid technology that combines radio and infrared to provide local relative positioning information when messages are transmitted between adjacent robots. Experiments with real robotic hardware show that EDSA is precise (misalignment of only 1.2° on average), robust (100% success rate for the experiments in this study) and fast (16.1 seconds on average from a distance of 80 cm). We show how the speed and precision of the new approach enable adaptive recruitment and connection in dynamic environments, a high degree of parallelism, and growth of a moving morphology.

Simultaneous localization and mapping (SLAM) is a prominent feature for autonomous robots operating in undefined environments. Applications areas such as consumer robotics appliances would clearly benefit from low-cost and compact SLAM implementations. The SLAM research community has developed several robust algorithms in the course of the last two decades. However, until now most SLAM demonstrators have relied on expensive sensors or large processing power, limiting their realms of application. Several works have explored optimizations into various directions; however none has presented a global optimization from the mechatronic to the algorithmic level. In this article, we present a solution to the SLAM problem based on the co-design of a slim rotating distance scanner, a lightweight SLAM software, and an optimization methodology. The scanner consists of a set of infrared distance sensors mounted on a contactless rotating platform. The SLAM algorithm is an adaptation of FastSLAM 2.0 that runs in real time on a miniature robot. The optimization methodology finds the parameters of the SLAM algorithm using an evolution strategy. This work demonstrates that an inexpensive sensor coupled with a low-speed processor are good enough to perform SLAM in simple environments in real time.

Collective and swarm robotics explores scenarios involving many robots running at the same time. A good platform for collective-robotic experiments should provide certain features among others: it should have a large battery life, it should be able to perceive its peers, and it should be capable of interacting with them. This paper presents the marXbot, a miniature mobile robot that addresses these needs. The marXbot uses differential-drive treels to provide rough-terrain mobility. The marXbot allows continuous experiments thanks to a sophisticated energy management and a hotswap battery exchange mechanism. The marXbot can self-assemble with peers using a compliant attachment mechanism. The marXbot provides high-quality vision, using two cameras directly interfaced with an ARM processor. Compared to the related work, the marXbot has better energy management, vision, and interaction capabilities. By allowing complex tasks in large environments for long durations, the marXbot opens new perspectives for the collective-robotic research.

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.

Mobile robots are said to be capable of self- assembly when they can autonomously form physical connections with each other. Despite the recent proliferation of self- assembling systems, little work has been done on using self- assembly 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.

An important goal of collective robotics is the design of control systems that allow groups of robots to accomplish common tasks by coordinating without a centralized control. In this paper, we study how a group of physically assembled robots can display coherent behavior on the basis of a simple neural controller that has access only to local sensory information. This controller is synthesized through artificial evolution in a simulated environment in order to let the robots display coordinated-motion behaviors. The evolved controller proves to be robust enough to allow a smooth transfer from simulated to real robots. Additionally, it generalizes to new experimental conditions, such as different sizes/shapes of the group and/or different connection mechanisms. In all these conditions the performance of the neural controller in real robots is comparable to the one obtained in simulation.

We present a first attempt to accomplish a simple object manipulation task using the self-reconfigurable robotic system swarm-bot. The number of modular entities involved, their global shape or size and their internal structure are not pre-determined, but result from a self-organized process in which the modules autonomously grasp each other and/or an object. The modules are autonomous in perception, control, action, and power. We present quantitative results, obtained with six physical modules, that confirm the utility of self-assembling robots in a concrete task

This article illustrates the methods and results of two sets of experiments in which a group of mobile robots, calleds-bots, are required to physically connect to each other, that is, to self-assemble, to cope with environmental conditions that prevent them from carrying out their task individually. The first set of experiments is a pioneering study on the utility of self-assembling robots to address relatively complex scenarios, such as cooperative object transport. The results of our work suggest that the s-bots possess hardware characteristics which facilitate the design of control mechanisms for autonomous self-assembly. The control architecture we developed proved particularly successful in guiding the robots engaged in the cooperative transport task. However, the results also showed that some features of the robots' controllers had a disruptive effect on their performances. The second set of experiments is an attempt to enhance the adaptiveness of our multi-robot system. In particular, we aim to synthesise an integrated (i.e., not-modular) decision-making mechanism which allows the s-bot to autonomously decide whether or not environmental contingencies require self-assembly. The results show that it is possible to synthesize, by using evolutionary computation techniques, artificial neural networks that integrate both the mechanisms for sensory-motor coordination and for decision making required by the robots in the context of self-assembly.

In this paper, we discuss the self-assembling capabilities of the swarm-bot, a distributed robotics concept that lies at the intersection between collective and self-reconfigurable robotics. A swarm-bot is comprised of 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 experiments in which we study the process that leads a group of s-bots to self-assemble. In particular, we present results of experiments in which we vary the number of s-bots (up to 16 physical robots), their starting configurations, and the properties of the terrain on which self-assembly takes place. In view of the very successful experimental results, swarm-bot qualifies as the current state of the art in autonomous self-assembly

This paper presents a new robotic concept, called SWARM-BOT, based on a swarm of autonomous mobile robots with self-assembling capabilities. SWARM-BOT takes advantage from collective and distributed approaches to ensure robustness to failures and to hard environment conditions in tasks such as navigation, search and transportation in rough terrain. One SWARM-BOT is composed of a number of simpler robots, called s-bots, physically interconnected. The SWARM-BOT is provided with self-assembling and self-reconfiguring capabilities whereby s-bots can connect and disconnect forming large flexible structures. This paper introduces the SWARM-BOT concept and describes its implementation from a mechatronic perspective.