Self-stabilizing robot formations over unreliable networks

We describe how a set of mobile robots can arrange themselves on any specified curve on the plane in the presence of dynamic changes both in the underlying ad hoc network and in the set of participating robots. Our strategy is for the mobile robots to implement a self-stabilizing virtual layer consisting of mobile client nodes, stationary Virtual Nodes (VNs), and local broadcast communication. The VNs are associated with predetermined regions in the plane and coordinate among themselves to distribute the client nodes relatively uniformly among the VNs' regions. Each VN directs its local client nodes to align themselves on the local portion of the target curve. The resulting motion coordination protocol is self-stabilizing, in that each robot can begin the execution in any arbitrary state and at any arbitrary location in the plane. In addition, self-stabilization ensures that the robots can adapt to changes in the desired target formation.National Science Foundation (U.S.) (Grant No. CNS-0614993

A Strategy for Multi-Robot Navigation

International audienceThe paper addresses the problem of trajectory regulation of driftless systems such that a stabilizing control input is assumed exists. The perturbed trajectory depends on a regulation control-input which must be designed such that the system's stability is preserved and some undesirable sets belonging to navigation area must be avoided. For the stability and regulation of a multi-robot system a converging attractive set around the target is constructed and a repulsive set around obstacles is emphasized. Taking into account a communication algorithm agents-agents to agents-target, we prove that the proposed regulation control-input preserves the navigation area invariance property and the system's stability. Simulation results illustrate the effectiveness of he proposed control algorithm

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Self-Stabilizing Message Routing in Mobile ad hoc Networks

We present a self-stabilizing algorithm for routing messages between arbitrary pairs of nodes in a mobile ad hoc network. Our algorithm assumes the availability of a reliable GPS service, which supplies mobile nodes with accurate information about real time and about their own geographical locations. The GPS service provides an external, shared source of consistency for mobile nodes, allowing them to label and timestamp messages, and thereby aiding in recovery from failures. Our algorithm utilizes a Virtual Infrastructure programming abstraction layer, consisting of mobile client nodes, virtual stationary timed machines called Virtual Stationary Automata (VSAs), and a local broadcast service connecting VSAs and mobile clients. VSAs are associated with predetermined regions in the plane, and are emulated in a self-stabilizing manner by the mobile nodes. VSAs are relatively stable in the face of node mobility and failure, and can be used to simplify algorithm development for mobile networks. Our routing algorithm consists of three subalgorithms: [(1)] a VSA-to-VSA geographical routing algorithm, [2] a mobile client location management algorithm, and [3] the main algorithm, which utilizes both location management and geographical routing. All three subalgorithms are self-stabilizing, and consequently, the entire algorithm is also self-stabilizing

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas

Abstraction and Control for Groups of Robots

This paper addresses the general problem of controlling a large number of robots required to move as a group. We propose an abstraction based on the definition of a map from the configuration space Q of the robots to a lower dimensional manifold A, whose dimension is independent of the number of robots. In this paper, we focus on planar fully actuated robots. We require that the manifold has a product structure A = G x S, where G is a Lie group, which captures the position and orientation of the ensemble in the chosen world coordinate frame, and S is a shape manifold, which is an intrinsic characterization of the team describing the “shape” as the area spanned by the robots. We design decoupled controllers for the group and shape variables. We derive controllers for individual robots that guarantee the desired behavior on A. These controllers can be realized by feedback that depends only on the current state of the robot and the state of the manifold A. This has the practical advantage of reducing the communication and sensing that is required and limiting the complexity of individual robot controllers, even for large numbers of robots

Distributed coordinate tracking control of multiple wheeled mobile robots

In this thesis, distributed coordinate tracking control of multiple wheeled-mobile robots is studied. Control algorithms are proposed for both kinematic and dynamic models. All vehicle agents share the same mechanical structure. The communication topology is leader-follower topology and the reference signal is generated by the virtual leader. We will introduce two common kinematic models of WMR and control algorithms are proposed for both kinematic models with the aid of graph theory. Since it is more realistic that the control inputs are torques so dynamic extension is studied following by the kinematics. Torque controllers are designed with the aid of backstepping method so that the velocities of the mobile robots converge to the desired velocities. Because of the fact that in practice, the inertial parameter of WMR maybe not exactly known or even unknown, so both dynamics with and without inertial uncertainties are considered in this thesis