Roderich Groß

Evolving Self-Organizing Behaviors for a Swarm-Bot

In this paper, we introduce a self-assembling and self-organizing artifact, called a swarm-bot, composed of a swarm of s-bots, mobile robots with the ability to connect to and to disconnect from each other. We discuss the challenges involved in controlling a swarm-bot and address the problem of synthesizing controllers for the swarm-bot using artificial evolution. Specifically, we study aggregation and coordinated motion of the swarm-bot using a physics-based simulation of the system. Experiments, using a simplified simulation model of the s-bots, show that evolution can discover simple but effective controllers for both the aggregation and the coordinated motion of the swarm-bot. Analysis of the evolved controllers shows that they have properties of scalability, that is, they continue to be effective for larger group sizes, and of generality, that is, they produce similar behaviors for configurations different from those they were originally evolved for. The portability of the evolved controllers to real s-bots is tested using a detailed simulation model which has been validated against the real s-bots in a companion paper in this same special issue.

Evolving Aggregation Behaviors in a Swarm of Robots

In this paper, we study aggregation in a swarm of simple robots, called s-bots, having the capability to self-organize and self- assemble to form a robotic system, called a swarm-bot. The aggregation process, observed in many biological systems, is of fundamental impor- tance since it is the prerequisite for other forms of cooperation that in- volve self-organization and self-assembling. We consider the problem of defining the control system for the swarm-bot using artificial evolution. The results obtained in a simulated 3D environment are presented and analyzed. They show that artificial evolution, exploiting the complex in- teractions among s-bots and between s-bots and the environment, is able to produce simple but general solutions to the aggregation problem.

The SWARM-BOTS project

This paper provides an overview of the SWARM-BOTS project, a robotic project sponsored by the Future and Emerging Technologies program of the European Commission. The paper illustrates the goals of the project, the robot prototype and the 3D simulator we built. It also reports on the results of experimental work in which distributed adaptive controllers are used to control a group of real, or simulated, robots so that they perform a variety of tasks which require cooperation and coordination.

Group Transport of an Object to a Target That Only Some Group Members May Sense

This paper addresses the cooperative transport of a heavy object, called prey, towards a sporadically changing target location by a group of robots. The study is focused on the situation in which some robots are given the opportunity to localize the target, while the others (called the blind ones) are not. We propose the use of relatively simple robots capable of self-assembling into structures which pull or push the prey. To enable a blind robot to contribute to the groups performance, it can locally perceive traction forces, and whether it is moving or not. The robot group is controlled in a distributed manner, using a modular control architecture. A collection of simple hand-coded and artificially evolved control modules is presented and discussed. For group sizes ranging from 2 to 16 and different proportions of blind robots within the group, it is shown that controlled by an evolved solution, blind robots make an essential contribution to the groups performance. The study is carried out using a physics-based simulation of a real robotic system that is currently under construction.

Self-assembly on demand in a group of physical autonomous mobile robots navigating rough terrain

Consider a group of autonomous, mobile robots with the ability to physically connect to one another (self-assemble). The group is said to exhibit functional self-assembly if the robots can choose to self-assemble in response to the demands of their task and environment [15]. We present the first robotic controller capable of functional self-assembly implemented on a real robotic platform. The task we consider requires a group of robots to navigate over an area of unknown terrain towards a target light source. If possible, the robots should navigate to the target independently. If, however, the terrain proves too difficult for a single robot, the robots should self-assemble into a larger group entity and collectively navigate to the target. We believe this to be one of the most complex tasks carried out to date by a team of physical autonomous robots. We present quantitative results confirming the efficacy of our controller. This puts our robotic system at the cutting edge of autonomous mobile multi-robot research.

Evolving a Cooperative Transport Behavior for Two Simple Robots

This paper addresses the problem of cooperative transport of an object by a group of two simple autonomous mobile robots called s-bots. S-bots are able to establish physical connections between each other and with an object called the prey. The environment consists of a flat ground, the prey, and a light-emitting beacon. The task is to move the prey as far as possible in an arbitrary direction by pulling and/or pushing it. The object cannot be moved without coordination. There is no explicit communication among s-bots; moreover, the s-bots cannot sense each other. All experiments are carried out using a 3D physics simulator. The s-bots are controlled by recurrent neural networks that are created by an evolutionary algorithm. Evolved solutions attained a satisfactory level of performance and some of them exhibit remarkably low fluctuations under different conditions. Many solutions found can be applied to larger group sizes, making it possible to move bigger objects.

Negotiation of goal direction for cooperative transport

In this paper, we study the cooperative transport of a heavy object by a group of robots towards a goal. We investigate the case in which robots have partial and noisy knowledge of the goal direction and can not perceive the goal itself. The robots have to coordinate their motion to apply enough force on the object to move it. Furthermore, the robots should share knowledge in order to collectively improve their estimate of the goal direction and transport the object as fast and as accurately as possible towards the goal. We propose a bio-inspired mechanism of negotiation of direction that is fully distributed. Four different strategies are implemented and their performances are compared on a group of four real robots, varying the goal direction and the level of noise. We identify a strategy that enables efficient coordination of motion of the robots. Moreover, this strategy lets the robots improve their knowledge of the goal direction. Despite significant noise in the robots’ communication, we achieve effective cooperative transport towards the goal and observe that the negotiation of direction entails interesting properties of robustness.

Occlusion-Based Cooperative Transport with a Swarm of Miniature Mobile Robots

This paper proposes a strategy for transporting a large object to a goal using a large number of mobile robots that are significantly smaller than the object. The robots only push the object at positions where the direct line of sight to the goal is occluded by the object. This strategy is fully decentralized and requires neither explicit communication nor specific manipulation mechanisms. We prove that it can transport any convex object in a planar environment. We implement this strategy on the e-puck robotic platform and present systematic experiments with a group of 20 e-pucks transporting three objects of different shapes. The objects were successfully transported to the goal in 43 out of 45 trials. When using a mobile goal, teleoperated by a human, the object could be navigated through an environment with obstacles. We also tested the strategy in a 3-D environment using physics-based computer simulation. Due to its simplicity, the transport strategy is particularly suited for implementation on microscale robotic systems.

Supervisory control theory applied to swarm robotics

Currently, the control software of swarm robotics systems is created by ad hoc development. This makes it hard to deploy these systems in real-world scenarios. In particular, it is difficult to maintain, analyse, or verify the systems. Formal methods can contribute to overcome these problems. However, they usually do not guarantee that the implementation matches the specification, because the system’s control code is typically generated manually. Also, there is cultural resistance to apply formal methods; they may be perceived as an additional step that does not add value to the final product. To address these problems, we propose supervisory control theory for the domain of swarm robotics. The advantages of supervisory control theory, and its associated tools, are a reduction in the amount of ad hoc development, the automatic generation of control code from modelled specifications, proofs of properties over generated control code, and the reusability of formally designed controllers between different robotic platforms. These advantages are demonstrated in four case studies using the e-puck and Kilobot robot platforms. Experiments with up to 600 physical robots are reported, which show that supervisory control theory can be used to formally develop state-of-the-art solutions to a range of problems in swarm robotics.

Division of Labour in Self-organised Groups

In social insect colonies, many tasks are performed by higher-order entities, such as groups and teams whose task solving capacities transcend those of the individual participants. In this paper, we investigate the emergence of such higher-order entities using a colony of up to 12 physical robots. We report on an experimental study in which the robots engage in a range of different activities, including exploration, path formation, recruitment, self-assembly and group transport. Once the robots start interacting with each other and with their environment, they self-organise into teams in which distinct roles are performed concurrently. The system displays a dynamical hierarchy of teamwork, the cooperating elements of which comprise higher-order entities. The study shows that teamwork requires neither individual recognition nor inter-individual differences, and as such might contribute to the ongoing debate on the role of such characteristics for the division of labour in social insects.