In this chapter, we demonstrate the e ectiveness of behavior-based control in facilitating the development and evaluation of multi-robot controllers that are: (1) robust to robot failures, and (2) easily modi ed to facilitate development of the controller variation that su ciently satis es the design requirements for the task. Our experimental focus here is distributed multi-robot collection, a class of tasks that includes de-mining and toxic waste clean-up. We demonstrate a basic, homogeneous multi-robot controller for the collection task, then show how to easily derive two heterogeneous, spatio-temporal variations with markedly di erent performance properties. We evaluate the desirability of these controllers with respect to design requirements involving inter-robot interference, time-to-completion, and energy expenditure. The data for evaluation come from experiments using four physical mobile robots performing the three variations of the collection task. 1

As research progresses in distributed robotic systems, more and more aspects of multi-robot systems are being explored. This article surveys the current state of the art in distributed mobile robot systems. Our focus is principally on research that has been demonstrated in physical robot implementations. We have identified eight primary research topics within multi-robot systems -- biological inspirations, communication, architectures, localization/mapping/exploration, object transport and manipulation, motion coordination, reconfigurable robots, and learning - and discuss the current state of research in these areas. As we describe each research area, we identify some key open issues in multi-robot team research. We conclude by identifying several additional open research issues in distributed mobile robotic systems.

Introduction Teams of robotic systems at first glance might appear to be more trouble than they are worth. Why not simply build one robot that is capable of doing everything we need? There are several reasons why two robots (or more) can be better than one: ffl Distributed Action: Many robots can be in many places at the same time ffl Inherent Parallelism: Many robots can do many, perhaps different things at the same time ffl Divide and Conquer: Certain problems are well suited for decomposition and allocation among many robots ffl Simpler is better: Often each agent in a team of robots can be simpler than a more comprehensive single robot solution No doubt there are more reasons as well. Unfortunately there are also drawbacks, in particular regarding coordination and elimination of interference. The degree of difficulty imposed depends heavily upon the task and the communication and control strategies chosen.

As research progresses in distributed robotic systems, more and more aspects of multi-robot systems are being explored. This special issue on Multi-Robot Systems provides a broad sampling of the research that is currently ongoing in the field of distributed mobile robot systems. To help categorize this research, we have identified seven primary research topics within multi-robot systems --- biological inspirations, communication, architectures, localization/mapping/exploration, object transport and manipulation, motion coordination, and reconfigurable robots. This editorial examines these research areas and discusses the special issue articles in this context. We conclude by identifying several additional open research issues in distributed mobile robotic systems.

We discuss a robotic system composed of Crystalline modules. Crystaline modules can aggregate together to form distributed robot systems. Crystalline modules can move relative to each other by expanding and contracting. This actuation mechanism permits automated shape metamorphosis. We describe the crystalline module concept and show the basic motions that enable a crystalline robot system to selfreconfigure. We present an algorithm for general selfreconfiguration and describe simulation experiments. 1

We wish to organize furniture in a room with a team of robots that can push objects. We show how coordinated pushing by robots can change the pose (position and orientation) of objects and then we ask whether planning, global control, and explicit communication are necessary for cooperatively changing the pose of objects. We answer in the negative and present, as witnesses, four cooperative manipulation protocols that use different amount of state, sensing, and communication. We analyze these protocols in the information invariant framework. We formalize the notion of resource tradeoffs for robot protocols and give the tradeoffs for the specific protocols discussed here. 1 Introduction We wish for robots to perform sophisticated tasks in structured environments, such as an assembly line, as well as unstructured ones, such as space, undersea, or outdoors. Such robots must have the ability to manipulate objects. Consider a manipulation task in which a couch is to be pushed out of a roo...

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 presents a geometric based approach for multiple mobile robot motion coordination 1 . All the robot paths being computed independently, we address the problem of coordinating the motion of the robots along their path in such a way they do not collide each other. The proposed algorithm is based on a bounding box representation of the obstacles in the so-called coordination diagram. The algorithm is resolution-complete but it is shown to be complete for a large class of inputs. Despite the exponential dependency of the coordination problem, the algorithm solves efficiently problems involving up to ten robots in worst case situations, and more than 100 robots in practical ones.

Abstract- A key problem in cooperative robotics is the maintenance of a geometric configuration during movement. To address this problem, the concept of a virtual structure is introduced. Control methods are developed to force an ensemble of robots to behave as if they were particles embedded in a rigid structure. The method was tested both using simulation and experimentation with a set of 3 robots. Results are presented which demonstrate that this approach is capable of achieving high precision movement which is fault tolerant and exhibits graceful degradation of performance. In addition, this algorithm does not require leader selection as in other cooperative robotic strategies. Finally, the method is highly flexible in the kinds of geometric formations that can be maintained.

Abstract—Inspired by the so-called “bugs ” problem from mathematics, we study the geometric formations of multivehicle systems under cyclic pursuit. First, we introduce the notion of cyclic pursuit by examining a system of identical linear agents in the plane. This idea is then extended to a system of wheeled vehicles, each subject to a single nonholonomic constraint (i.e., unicycles), which is the principal focus of this paper. The pursuit framework is particularly simple in that the identical vehicles are ordered such that vehicle pursues vehicle CImodulo. In this paper, we assume each vehicle has the same constant forward speed. We show that the system’s equilibrium formations are generalized regular polygons and it is exposed how the multivehicle system’s global behavior can be shaped through appropriate controller gain assignments. We then study the local stability of these equilibrium polygons, revealing which formations are stable and which are not. Index Terms—Circulant matrices, cooperative control, multiagent systems, pursuit problems. I.