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

An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of observing the movements of targets navigating in a bounded area of interest. A key research issue in these problems is that of sensor placement -- determining where sensors should be located to maintain the targets in view. In complex applications involving limited-range sensors, the use of multiple sensors dynamically moving over time is required. In this paper, we investigate the use of a cooperative team of autonomous sensor-based robots for the observation of multiple moving targets. In other research, analytical techniques have been developed for solving this problem in complex geometrical environments. However, these previous approaches are very computationally expensive - at least exponential in the number of robots -- and cannot be implemented on robots operating in real-time. Thus, this paper reports on our studies of a simpler problem involving uncluttered environments -- those with either no obstacles or with randomly distributed simple convex obstacles. We focus primarily on developing the on-line distributed control strategies that allow the robot team to attempt to minimize the total time in which targets escape observation by some robot team member in the area of interest. This paper first formalizes the problem (which we term CMOMMT for Cooperative Multi-Robot Observation of Multiple Moving Targets) and discusses related work. We then present a distributed heuristic approach (which we call A-CMOMMT) for solving the CMOMMT problem that uses weighted local force vector control. We analyze the effectiveness of the resulting weighted force vector approach by comparing it to three other approaches. We present the results of our experiments in...

Real-world applications that are ideal for robotic solutions are very complex and challenging. Many of these applications are set in dynamic environments that require capabilities distributed in functionality, space, or time. These applications, therefore, often require teams of robots to work together cooperatively to successfully address the mission. While much research in recent years has addressed the issues of autonomous robots and multi-robot cooperation, current robotics technology is still far from achieving many of these real world applications. We believe that two primary reasons for this technology gap are that (1) previous work has not adequately addressed the issues of fault tolerance and adaptivity in multi-robot teams, and (2) existing robotics research is often geared at specific applications, and is not easily generalized to different, but related, applications. This paper addresses these issues by first describing the design issues of key importance in these real-world cooperative robotics applications -- fault tolerance, reliability, adaptivity, and coherence. We then present a general architecture addressing these design issues -- called ALLIANCE -- that facilitates multi-robot cooperation of small- to mediumsized teams in dynamic environments, performing missions composed of loosely coupled subtasks. We illustrate the generality of this architecture by describing two very different proof-of-concept implementations of this architecture: a janitorial service mission, and a bounding overwatch mission.

We present a distributed planar object manipulation algorithm inspired by human behavior. The system, which we call pusher-watcher, enables the cooperative manipulation of large objects by teams of autonomous mobile robots. The robots are not equipped with gripping devices, but instead move objects by pushing against them. The pusher robots have no global positioning information, and cannot see over the object; thus a watcher robot has the responsibility for leading the team (and object) to the goal, which only it can perceive. The system is entirely distributed, with each robot under local control. Through the use of Murdoch, an auction-based resource-centric general purpose task-allocation framework, roles in the team are automatically assigned in an efficient manner. Further, robot failures are easily tolerated and, when possible, automatically recovered. We present results and analysis from a battery of experiments with pusher-watcher implemented on a group of Pioneer 2 mobile robots.

In this paper we present an approach to controlling transitions in multi-robot tasks which have been modelled as a linear series of steps. A box-pushing task is described as a sequence of sub-tasks with a separate controller designed for each step using finite state automata theory. Perceptual cues are formed by concatenating binary variables which represent locally sensed stimuli into boolean vectors used to specifiy transitions between sub-task steps. The approach is designed for a redundant set of homogeneous mobile robots equipped with simple sensors and stimulus-response behaviours. A set of perceptual cues used in box-pushing are designed and tested on 10 physical mobile robots. It is argued that perceptual cues and finite state automata offers a new approach to environment-specific task modelling in collective robotics. 1 Introduction Recent interest in accomplishing tasks with multiple mobile robots has led to a number of canonical tasks on which to test theories in multi-robo...

many security, surveillance, and reconnaissance tasks is that of monitoring (or observing) the movements of targets navigating in a bounded area of interest. A key research issue in these problems is that of sensor placement --- determining where sensors should be located to maintain the targets in view. In complex applications involving limited-range sensors, the use of multiple sensors dynamically moving over time is required. In this paper, we investigate the use of a cooperative team of autonomous sensor-based robots for the observation of multiple moving targets. We focus primarily on developing the distributed control strategies that allow the robot team to attempt to minimize the total time in which targets escape observation by some robot team member in the area of interest. This paper first formalizes the problem and discusses related work. We then present a distributed approximate approach to solving this problem that combines low-level multi-robot control with higher-level reasoning control based on the ALLIANCE formalism. We analyze the effectiveness of our approach by comparing it to three other feasible algorithms for cooperative control, showing the superiority of our approach for a large class of problems.

An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of observing (or monitoring) the movements of targets navigating in a bounded area of interest. A key research issue in these problems is that of sensor placement --- determining where sensors should be located to maintain the targets in view. In complex applications involving limited-range sensors, the use of multiple sensors dynamically moving over time is required. In this article, we investigate the use of a cooperative team of autonomous sensor-based robots for the observation of multiple moving targets (a problem that we term CMOMMT). We focus primarily on developing the distributed control strategies that allow the robot team to attempt to maximize the collective time during which each target is being observed by at least one robot team member in the area of interest. Our initial efforts on this problem address the aspects of distributed control in robot teams with e...

Previous research in cooperative robotics has investigated several possible ways of coordinating the actions of cooperative teams --- from implicit cooperation through sensory feedback to explicit cooperation using the exchange of communicated messages. These various approaches differ in the extent to which robot team members are aware of, or recognize the actions of their teammates and the extent to which they use this information to effect their own actions. The research described in this paper investigates this issue of robot awareness of team member actions and its effect on cooperative team performance by examining the results of a series of experiments on teams of mobile robots performing a puck moving mission. In these experiments, we vary the team size (and thus the level of redundancy in team member capabilities) and the level of awareness robots have of their teammates' current actions and evaluate the team's performance using two metrics: time and energy. The results indicat...

In practical applications of robotics, it is usually quite difficult, if not impossible, for the system designer to fully predict the environmental states in which the robots will operate. The complexity of the problem is further increased when dealing with teams of robots which themselves may be incompletely known and characterized in advance. It is thus highly desirable for robot teams to be able to adapt their performance during the mission due to changes in the environment, or to changes in other robot team members. In previous work [40, 44], we introduced a behavior-based mechanism --- called the ALLIANCE architecture --- that facilitates the fault tolerant cooperative control of multi-robot teams. However, this previous work did not address the issue of how to dynamically update the control parameters during a mission to adapt to ongoing changes in the environment or in the robot team, and to ensure the efficiency of the collective team actions. In this paper, we address this iss...