ALLIANCE is a software architecture that fa- cilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behavior-based architecture that incorporates the use of mathematically-modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.

There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of collective robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations. 1

Designing and implementing cooperative group behaviors for robots is considered something of a black art involving an extensive amount of reprogramming and parameter adjustment. What seems to be lacking is a pragmatic, practical, general-purpose tool that would both guide the design and structure the evaluation of controllers for distributed real-world multi-robot tasks. In this paper, we propose the use of interference between robots as one such simple tool for designing and evaluating multi-robot controllers. We explore how key issues in multi-robot control can be addressed using interference, a directly measurable property of a multi-robot system. We discuss how behavior arbitration schemes, i.e., the choice of controllers, can be made and adjusted using interference. As an experimental example, we demonstrate three different implementations of a collection clean-up (foraging) task using four physical mobile robots, and present analyses of the experimental data gathered from trials ...

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.

While terminology and some concepts of behavior-based robotics have become widespread, the central ideas are often lost as researchers try to scale behavior to higher levels of complexity. "Hybrid systems" with model-based strategies that plan in terms of behaviors rather than simple actions have become common for higherlevel behavior. We claim that a strict behavior-based approach can scale to higher levels of complexity than many robotics researchers assume, and that the resulting systems are in many cases more efficient and robust than those that rely on "classical AI" deliberative approaches. Our focus is on systems of cooperative autonomous robots in dynamic environments. We will discuss both claims that deliberation and explicit communication are necessary to cooperation and systems that cooperate only through environmental interaction. In this context we introduce three design principles for complex cooperative behavior - minimalism, statelessness and tolerance - and present a ...

This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. We describe a novel behaviorbased, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled, largely independent tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since such cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills...

This work demonstrates the application of the distributed behavior-based approach [1] to generating a multi-robot controller for a group of mobile robots performing a clean-up and collection task. The paper studies a territorial approach to the task in which the robots are assigned individual territories that can be dynamically resized if one of the robots missfunctions, permitting the completion of the task. The described controller is implemented on a group of four IS Robotics R2e mobile robots. Using a collection of experimental robot data, we empirically derive and demonstrate most effective foraging in our domain, and show the decline of performance of the space division strategy with increased group size.

This paper builds on a previous review of significant research on adaptive behavior in animats. It summarizes the current state of the art and suggests some directions likely to provide interesting results in the near future. 1 Introduction An animat is a simulated animal or a real robot whose rules of behavior are inspired by those of animals. It is usually equipped with sensors, with actuators, and with a behavioral control architecture that allow it to react or to respond to variations in its environment (internal or external), notably to those that might impair its chances of survival. The behavior of an animat is what the animat does. This is characterized by a sequence of actions which reflects the dynamic interplay between the animat and its environment, mediated through the animat's sensors and actuators. The behavior of an animat is adaptive so long as it allows the animat to survive or to fulfill its mission. This requires that the animat's essential variables be monitored a...