Abstract — Real life deployment of robot formation cannot assume that robots are going to be correctly positioned to move in a particular configuration. To do so, we propose an approach that allows the group to determine autonomously the most appropriate assignment of positions in the formation. Our approach is distributed and uses directional visual perception to localize robots. Inter-robot communication allows them to share information on which robots are nearby, so that each can evaluate it ability to be the conductor of the group and assign formation positions to the other robots by minimizing repositioning. The assignment search is done using a distributed bounded depth-first with pruning search. The robot with the best score is selected as the conductor, and the other robots received from the conductor their assignment in the formation. Validation of our work is done in simulation and with Pioneer 2 robots. I.

In this paper, we presented a review on the current control issues and strategies on a group of unmanned autonomous vehicles/robots formation. Formation control has broad applications and becomes an active research topic in the recent years. In this paper, we attempt to review the key issues in formation control with a focus on the main control strategies for formation control under different kinds of scenarios. Then, we point out some important open questions and the possible future research directions on formation control. This paper contributes with a new and interesting consideration on formation control and its application in distributed parameter systems. We pointed out that formation control should be classified as formation regulation control and formation tracking control, similar to regulator and tracker in conventional control.

Abstract — This paper addresses the problem of resource allocation in formations of mobile robots localizing as a group. Each robot receives measurements from various sensors that provide relative (robot-to-robot) and absolute positioning information. Constraints on the sensors ’ bandwidth, as well as communication and processing requirements, limit the number of measurements that are available or can be processed at each time step. The localization uncertainty of the group, determined by the covariance matrix of the equivalent continuous-time system at steady state, is expressed as a function of the sensor measurements’ frequencies. The trace of the submatrix corresponding to the position estimates is selected as the optimization criterion, under linear constraints on the measuring frequency of each sensor and the cumulative rate of EKF updates. This formulation leads to a convex optimization problem whose solution provides the sensing frequencies, for each sensor on every robot, required in order to maximize the positioning accuracy for the group. Simulation experiments are presented that demonstrate the applicability of this method and provide insight into the properties of the resource-constrained cooperative localization problem. I.

Abstract—This paper implements several methods for performing vision-based formation flight control of multiple aircraft in the presence of obstacles. No information is communicated between aircraft, and only passive 2-D vision information is available to maintain formation. The methods for formation control rely either on estimating the range from 2-D vision information by using Extended Kalman Filters or directly regulating the size of the image subtended by a leader aircraft on the image plane. When the image size is not a reliable measurement, especially at large ranges, we consider the use of bearing-only information. In this case, observability with respect to the relative distance between vehicles is accomplished by the design of a time-dependent formation geometry. To improve the robustness of the estimation process with respect to unknown leader aircraft acceleration, we augment the EKF with an adaptive neural network. 2-D and 3-D simulation results are presented that illustrate the various approaches.

In many multi-robot applications, the specific assignment of goal configurations to robots is less important than the overall behavior of the robot formation. In such cases, it is convenient to define a permutation-invariant multi-robot formation as a set of robot configurations, without assigning specific configurations to specific robots. For the case of robots that translate in the plane, we can represent such a formation by the coefficients of a complex polynomial whose roots represent the robot configurations. Since these coefficients are invariant with respect to permutation of the roots of the polynomial, they provide an effective representation for permutation-invariant formations. In this paper, we extend this idea to build a full representation of a permutation-invariant formation space. We describe the properties of the representation, and show how it can be used to construct collision-free paths for permutationinvariant formations.

In certain multi-robot systems, the physical limitations of the individual robots can be overcome using self-assembly—the autonomous creation of physical connections between individual robots to form a larger composite robotic entity. However, existing robotic systems capable of self-assembly have little or no control over the morphology of the self-assembled entities. This restricts the adaptability of such systems, since robots can carry out certain tasks more efficiently if their morphology is specialized to the task. In this paper, we extend the distributed mechanism presented in (Christensen et al. in IEEE Robot. Autom. Mag. 14(4):18–25, 2007) that allows autonomous mobile robots to self-assemble into specific morphologies. We present a simple language, SWARMORPH-script, that allows for concise descriptions of the rules that govern the distributed morphology growth process. Local visual communication allows physically connected robots to send and receive strings. A string can be a rule identifier that triggers execution of predefined logic for extending a morphology. Alternatively, whole scripts can be communicated and subsequently executed on the receiving robot. On real self-propelled robots capable of self-assembly, we demonstrate how specific morphologies can be constructed, how the size of a morphology can be regulated, and how multiple morphologies can be assembled. We also show how the transmission of entire scripts gives the robots the capacity to participate in the formation of morphologies of which they had no a priori knowledge.

Abstract — This paper focuses on leader-follower formations of mobile robots equipped with panoramic cameras and extend earlier works in the literature addressing both the visionbased localization and control problems. First, a new sufficient analytical condition for localizability is proved and used to shed light on the geometrical meaning of formation localization using uncalibrated vision sensors, here performed with the Unscented Kalman Filter. Second, we design a feedback control law based on dynamic extension in order to extend the applicability of our control scheme also to the case of distant robots. I.

In this paper, we present a novel approach for representing formation structures in terms of queues and formation vertices, rather than with nodes, as well as the introduction of the new concept of artificial potential trenches, for effectively controlling the formation of a group of robots. The scheme improves the scalability and flexibility of robot formations when the team size changes, and at the same time, allows formations to adapt to obstacles. Furthermore, for multirobot teams to operate successfully in real and unstructured environments, the instant goal method is used to effectively solve the local minima problem.

We consider the problem of having a group of nonholonomic mobile robots equipped with omnidirectional cameras maintain a desired leader-follower formation. Our approach is to translate the formation control problem from the configuration space into a separate visual servoing task for each follower. We derive the equations of motion of the leader in the image plane of the follower and propose two control schemes for the follower. The first one is based on feedback linearization and is either string stable or leaderto -formation stable, depending on the sensing capabilities of the followers. The second one assumes a kinematic model for the evolution of the leader velocities and combines a Luenberger observer with a linear control law that is locally stable. We present simulation results evaluating our visionbased follow-the-leader control strategies.

Abstract — This paper considers the problem of merging of more than two (minimally) rigid formations which do not have any common agent to obtain a single (minimally) rigid formation in ℜ 2 and ℜ 3. Following previously developed strategies for sequential merging of two rigid formations, a new set of enhanced merging operations is developed. They can be performed in a formalized meta-formation framework, where the individual rigid formations are considered as metavertices and they can be merged into a meta-formation. These operations for growing meta-formations offer a level of control to the merging quality and optimality, in the sense of minimizing the number of meta-edges (that is, edges between different meta-vertices) required. It is also proved that all minimally rigid meta-formations in ℜ 2 can be obtained by successively merging two or more meta-vertices using the proposed set of meta-operations. I.