This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Abstract. Consider a system of multiple mobile robots in which each robot, at infinitely many unpredictable time instants, observes the positions of all the robots and moves to a new position determined by the given algorithm. The robots are anonymous in the sense that they all execute the same algorithm and they cannot be distinguished by their appearances. Initially they do not have a common x-y coordinate system. Such a system can be viewed as a distributed system of anonymous mobile processes in which the processes (i.e., robots) can “communicate ” with each other only by means of their moves. In this paper we investigate a number of formation problems of geometric patterns in the plane by the robots. Specifically, we present algorithms for converging the robots to a single point and moving the robots to a single point in finite steps. We also characterize the class of geometric patterns that the robots can form in terms of their initial configuration. Some impossibility results are also presented.

This paper presents a new sensing modality for multirobot exploration. The approach is based on using a pair of robots that observe each other, and act in concert to reduce odometry errors. We assume the robots can both directly sense nearby obstacles and see each other. The proposed approach improves the quality of the map by reducing the inaccuracies that occur over time from dead reckoning errors. Furthermore, by exploiting the ability of the robots to see each other, we can detect opaque obstacles in the environment independently of their surface reectance properties. Two dierent algorithms, based on the size of the environment, are introduced, with a complexity analysis, and experimental results in simulation and with real robots. Keywords: Exploration, Mapping, Multiple Robots, Cooperative Localization. 1. Introduction In this paper we discuss the benets of cooperative localization during the exploration of a large environment. A new

The distributed coordination and control of a set of autonomous mobile robots is a problem widely studied in a variety of fields, such as engineering, artificial intelligence, artificial life, robotics. Generally, in these areas the problem is studied mostly from an empirical point of view. In contrast, we aim to understand the fundamental limitations on what a set of autonomous mobile robots can achieve. In this paper we describe the current investigations on what autonomous mobile robots can and cannot do with respect to some coordination problems.

Abstract—This paper presents a behavior-based approach to formation maneuvers for groups of mobile robots. Complex formation maneuvers are decomposed into a sequence of maneuvers between formation patterns. The paper presents three formation control strategies. The first strategy uses relative position information configured in a bidirectional ring topology to maintain the formation. The second strategy injects interrobot damping via passivity techniques. The third strategy accounts for actuator saturation. Hardware results demonstrate the effectiveness of the proposed control strategies. Index Terms—Behavioral methods, coordinated control, formations, mobile robots, passivity.

This paper studies fault tolerant algorithms for the problem of gathering N au-tonomous mobile robots. A gathering algorithm, executed independently by each robot, must ensure that all robots are gathered at one point within nite time. In a failure-prone system, a gathering algorithm is required to successfully gather the nonfaulty robots, independently of the behavior of the faulty ones. Both crash and Byzantine faults are considered. It is rst observed that most existing algorithms fail to operate correctly in a setting allowing crash failures. Subsequently, an algorithm tolerant against one crash-faulty robot in a system of three or more robots is presented. It is then observed that all known algorithms fail to operate correctly in a system prone to Byzantine faults, even in the presence of a single fault. Moreover, it is shown that in an asynchronous environment it is impossible to perform a successful gathering in a 3-robot system, even if at most one of them might fail in a Byzantine manner. Thus, the problem is studied in a fully synchronous system. An algorithm is provided in this model for gathering N 3 robots with at most a single faulty robot, and a more general gathering algorithm is given in an N-robot system with up to f faults, where N 3f +1.

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.

An optimization problem that naturally arises in the study of "swarm robotics" is to wake up a set of "asleep" robots, starting with only one "awake" robot. One robot can only awaken another when they are in the same location. As soon as a robot is awake, it assists in waking up other robots. The goal is to compute an optimal awakening schedule such that all robots are awake by time t , for the smallest possible value of t . We consider both scenarios on graphs and in geometric environments. In the graph setting, robots sleep at vertices and there is a length function on the edges. An awake robot can travel from vertex to vertex along edges, and the length of an edge determines the time it takes to travel from one vertex to the other. While this problem bears some resemblance to problems from various areas in combinatorial optimization such as routing, broadcasting, scheduling and covering, its algorithmic characteristics are surprisingly different. We prove that the problem is NP-hard, even for the special case of star graphs. We also establish hardness of approximation, showing that it is NP-hard to obtain an approximation factor better than 5/3, even for graphs of bounded degree. These lower bounds are complemented with several algorithmic results. We present a simple on-line algorithm that is O(log)-competitive for graphs with maximum degree . Other results include algorithms that require substantially more sophistication and development of new techniques: (1) The natural greedy strategy on star graphs has a worst-case performance of 7/3, which is tight. (2) There exists a PTAS for star graphs. (3) For the problem Dept. of Appl. Math. and Statistics, SUNY Stony Brook, NY 11794-3600, festie, jsbmg@ams.sunysb.edu. y Dept. of Computer Science, SUNY St...

In this paper we study the problem of gathering in the same location of the plane a collection of identical oblivious mobile robots. Previous investigations have focused mostly on the unlimited visibility setting, where each robot can always see all the other ones, regardless of their distance. In the more difficult and realistic setting where the robots have limited visibility, the existing algorithmic results are only for convergence (towards a common point, without ever reaching it) and only for synchronous environments, where robots’ movements are assumed to be performed instantaneously. In contrast, we study this problem in a totally asynchronous setting, where robots ’ actions, computations, and movements require a finite but otherwise unpredictable amount of time. We present a protocol that allows anonymous oblivious robots with limited visibility to gather in the same location in finite time, provided they have orientation (i.e., agreement on a coordinate system). Our result indicates that, with respect to gathering, orientation is at least as powerful as instantaneous movements.

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...