this paper we report on our recent work evolving controllers for robots which are required to work as a team. The word team ' has been used in a variety of senses in both the multi-robot and the ethology literature, so it is appropriate to start the paper with a denition. We will adopt the denition given by Anderson & Franks (2001) in their recent review of team behaviour in animal societies. They identify three dening features of team behaviour. First, individuals make dierent contributions to task success, i.e. they must perform dierent sub-tasks or roles (this does not preclude more than one individual adopting the same role; there may be more individuals than roles). Second, individual roles or sub-tasks are interdependent (or interlocking'), requiring structured cooperation; individuals operate concurrently, coordinating their dierent contributions in order to complete the task. Finally, a team's organizational structure persists over time, although its individuals may be substituted or swap roles (Anderson & Franks 2001)

This paper proposes a distributed algorithm by which a collection of mobile robots roaming on a plane move to form a circle. The algorithm operates under the premises that robots (1) are unable to recall past actions and observations (i.e., oblivious), (2) cannot be distinguished from each others (i.e., anonymous), (3) share no common sense of direction, and (4) are unable to communicate in any other ways than by observing each others position.

We develop and analyze algorithms for dispersing a swarm of primitive robots in an unknown environment, R. The primary objective is to minimize the makespan, that is, the time to fill the entire region. An environment is composed of pixels that form a connected subset of the integer grid. There is at most one robot per pixel and robots move horizontally or vertically at unit speed. Robots enter R by means of k ≥ 1 door pixels. Robots are primitive finite automata, only having local communication, local sensors, and a constant-sized memory. We first give algorithms for the single-door case...

This paper deals with systems of multiple mobile robots each of which observes the positions of the other robots and moves to a new position so that eventually the robots form a circle. In the model we study, the robots are anonymous and oblivious, in the sense that they cannot be distinguished by their appearance and do not have a common x-y coordinate system, while they are unable to remember past actions. We propose a new distributed algorithm for circle formation on the plane. We prove that our algorithm is correct and provide an upper bound for its performance. In addition, we conduct an extensive and detailed comparative simulation experimental study with the DK algorithm described in [7]. The results show that our algorithm is very simple and takes considerably less time to execute than algorithm DK. 1 Introduction, Our Results and Related Work Lately, the field of cooperative mobile robotics has received a lot of attention from various research institutes and industries. A focus of these research and development activities is that of distributed motion coordination, since it allows the robots to form certain patterns and move in formation

The control and coordination of mobile robots in groups that can freely cooperate and move on a plane is a widely studied topic in distributed robotics. In this paper, we focus on the flocking problem: there are two kinds of robots: the leader robot and the follower robots. The follower robots are required to follow the leader robot wherever it goes (following), while keeping a formation they are given in input (flocking). A novel scheme is proposed based on the relative motion theory. Extensive theoretical analysis and simulation results demonstrate that this scheme provides the follower robots an efficient method to follow the leader as soon as possible with the shortest path. Furthermore, this scheme is scalable, and the processing load for every robot is not increased with the addition of more robots.

Self-organization is a computing paradigm in which participating entities proceed to execute a global goal strictly based on local information. In population dynamics, the sense of togetherness (due to social bindings or a common confinement) experienced by a group of individuals (i.e. „crowd group‟) is an interesting phenomenon to explore in the context of self-organization. Given a mechanism supporting spatial awareness, many settings require individuals belonging to a group, not only, to stay together (togetherness), but also to account for personal goals (dispersion). Self-organization can help individuals within such a group to stay together and having dispersed at the same time, togetherness being the primary requirement. In this paper, we discussed the parameters defining togetherness and dispersion within a spatially aware crowd group. In this context, the factors affecting the interplay between togetherness and dispersion were examined and maximum tolerable limits of dispersion were tailored in diverse settings of collaboration range, number of individuals willing to diverge and density of a crowd group. Simulation results provide insight into the interplay between these parameters, hence resolving operational dependencies.

Abstract — In this paper, we consider problems of coordinating and controlling the motion of a group of autonomous mobile robots engaged on common tasks. In particular, we present simulation results of a distributed algorithm for converging autonomous mobile robots toward the formation of a uniform circle. The algorithm takes a configuration wherein robots, already located on a circle, move so that they are eventually located at regular intervals on the boundary of the circle. We have simulated the algorithm under various parameters in order to analyze its convergence. Currently, our results show how the convergence of the algorithm is affected by the parameters of the system.

In this paper we propose and prove correct a new self-stabilizing velocity agreement (flocking) algorithm for oblivious and asynchronous robot networks. Our algorithm allows a flock of uniform robots to follow a flock head emergent during the computation whatever its direction in plane. Robots are asynchronous, oblivious and do not share a common coordinate system. Our solution includes three modules architectured as follows: creation of a common coordinate system that also allows the emergence of a flock-head, setting up the flock pattern and moving the flock. The novelty of our approach steams in identifying the necessary conditions on the flock pattern placement and the velocity of the flock-head (rotation, translation or speed) that allow the flock to both follow the exact same head and to preserve the flock pattern. Additionally, our system is self-healing and self-stabilizing. In the event of the head leave (the leading robot disappears or is damaged and cannot be recognized by the other robots) the flock agrees on another head and follows the trajectory of the new head. Also, robots are oblivious (they do not recall the result of their previous computations) and we make no assumption on their initial position. The step complexity of our solution is O(n).

Stabilizing flocking via leader election in robot networks