Many surveillance and reconnaissance tasks make use of multi-cameras in order to ensure that a particular mission is accomplished. These networks of cameras are useful as they can reduce the cost of human observers, are continuously observant (unlike humans who may fall asleep on the job), and can be implemented for a fairly low cost. However, in many scenarios, it does not make sense or may not be possible to have a fixed camera installation because the surveillance may only be needed for a short duration or it may take too long to do a proper install and observation is needed now. In terms of short terms and immediacy, mobile robots acting as a camera network provide an interesting middle ground. They can be deployed quickly to cover immediate needs, and they can be packed up and moved to another area if needs change. However, as the duration of the mission in which they are used increases, the robotic team will run out of power. This paper addresses some of the issues with keeping a surveillance team active while their batteries drain. Multiple task-reallocation methods are used in conjunction with an analysis of the effects of fixed vs mobile docking stations. Simulations were run requiring the team to provide camera coverage of a group of mobile “pedestrians” moving dynamically through a scene and the results are presented.

In order to increase the effectiveness of robotic systems, the robots must be able to negotiate a variety of terrains. In urban environments this task becomes challenging as environments built for humans often have impediments such as stairs and thresholds which may be difficult or impossible for wheeled or tracked vehicles to go over. This is further complicated in search and rescue scenarios where debris and rubble from collapsed structures may further complicate the environment. In order to address these limitations a novel robotic platform, the Loper, has been developed. The Loper utilizes a Tri-lobe wheel and a compliant chassis in order to traverse difficult terrain. In addition, multiple gait configurations of the Tri-lobe wheel enable the Loper to overcome a variety of obstacles, both indoors and out.

Effective robotic autonomy requires an accurate estimation of the remaining power that the robot is carrying. There are a number of methods to estimate the remaining capacity of the robot's batteries. The accuracy of these approaches varies depending upon the chemical composition of the batteries as well as the means by which the monitoring is conducted. In this paper, an overview of various battery capacity estimation methodologies will be presented as well as a discussion of a specific implementation utilized on robotic platforms developed at the Center for Distributed Robotics at the University of Minnesota. This approach involves the novel use of fuel-gauging electronics for mobile robotic platforms. Experiments were conducted to show the accuracy of this method for both charge and discharge of the polymer Lithium-ion batteries in use.

This paper presents a new vision-based leader-follower formation algorithm where the leader's trajectory is unknown to the robots which are following. Formation schemes in straight lines and diagonal formations are introduced which are both stable and observable in the presence of limited views. The algorithms are novel since they only use local image measurements through a pinhole camera to estimate the leader's position. This approach does not require specialized markings nor extensive robot communications. The algorithms are also decentralized. We apply an input-output feedback linearization for system stability and utilize an Extended Kalman Filter (EKF) for estimation. Simulations illustrate how the proposed formation controls work. Real experiments utilizing multiple miniature robots are also presented and illustrate the challenges associated with noisy images in real-world applications.

Robotic teams are often proposed for solving a number of problems, ranging from exploring unknown environments to monitoring areas for security or environmental contamination. These teams are composed of individual robots which may lack the capabilities to complete a task on their own. One critical capability required by teams regardless of the mission is the ability to have sufficient battery life to remain active for the duration of the mission. We present an approach for maintaining battery life by developing a hierarchical team composed of deployable robots and docking stations. Unlike other approaches, the approach presented here focuses on docking stations supporting multiple deployed robots simultaneously. In order to do so the docking stations must continually optimize their locations with respect to the robots in need of service. Discussion of the optimization is presented, along with simulation in multiple environments to illustrate the scalability of the approach to large robotic teams. The on-going transition of this algorithm to actual hardware is also discussed.

The use of cameras is becoming more prevalent by the day owing to the variety of applications they have. However, each application requires a specific placement of the cameras for best performance. Therefore, determining this placement has been a problem of much work in the field of computer vision. However, most of the current approaches deal with a scene that does not change once the cameras have been placed. In this paper a system is developed and successfully tested that can not only distribute cameras around a scene such that the observability is improved, but can reorganize the cameras if the pattern of activity within a scene changes with time. The cameras can be distributed in either two or three dimensional space, and this was tested with the use of mobile robotic cameras and stationary cameras.

The purpose of this paper is to describe the Loper, a multi-purpose robotic platform under development at the University of Minnesota's Center for Distributed Robotics. Leper's unique Tri-lobe wheel design and highly compliant chassis make the platform especially suited for overcoming many of the challenges associated with search operations in urban settings. The mechanically simple design and use of commercially available components make Loper easily maintainable. The platform also features long operational time, onboard sensor processing, dedicated motion control, and four reconfigurable sensor bays.

Within the fields of law enforcement and urban search and rescue, there is always a need to obtain information from areas that may be hard to reach or unsafe to enter. One method of obtaining this reconnaissance information is to deploy a robot as a projectile. This may be accomplished with mechanical aids or simply by throwing the robot manually. This rapid deployment method has the ability to attain locations inaccessible to other technologies. The miniature nature of the presented design has the ability to operate discretely and avoid detection, making it desirable for law enforcement. In the case of urban search and rescue, the diminutive form minimizes the impact on potentially unsound structures. During the course of deployment, unexpected impacts and drops are inevitable, generating a need for an impact invariant design. Design decisions to create this system are presented, and experimental validation of design aspects is discussed

Distributed robotic teams have long been touted as potential means to avoid sending humans into harmful situations. The ability of robotic teams to operate for extended periods without the fatigue human teams can experience, coupled with the ability to transport a variety of sensing and manipulation equipment and reducing costs of operation make them an attractive solution. Limited sensing capabilities, power, and mobility of individual robotic platforms can be overcome by forming teams of heterogeneous robots. This work addresses the power limitations associated with individual robots, which have finite amounts of power, and thus limited operational lifetimes. This work presents a method by which mobile docking stations can optimize their locations in order to maximize the power available to the deployed robots. Simulated results are presented in which teams of docking stations continuously recover and recharge a much larger team of deployed robots. It is assumed that the deployed robots are able to maintain a communication link between themselves and the docking station. This communication link is used to provide position information and available power to the docking stations. The communication link may be direct from the robot to docking station or it may require the use of ad hoc routing through other deployed robots

Large scale robotic teams are capable of working independently or cooperatively to carry out a variety of missions. However, for large teams of robots to function for extended periods of time, the individual members of a team must be able to generate or find energy to re-supply themselves. One approach to providing power for a robotic team is to couple larger systems with significant energy reserves so that the smaller systems can be recharged directly from the larger. This paper presents an implementation of such an approach. Here, a modular docking station is given locomotion through the cooperation of two larger robots. The docking station is capable of transporting, deploying, retrieving, and recharging many smaller robots. The kinematic model which will govern the cooperation of the maneuvering robots and will be used to develop control is presented and discussed. The design of the individual bays of the docking station and how they facilitate the deployment, recovery, and recharge of the smaller robots is also presented. The development of this system makes possible a number of applications, including autonomous long-term environmental monitoring and reconnaissance in various locations

The performance of systems for human activity recognition depends heavily on the placement of cameras observing the scene. This work addresses the question of the optimal placement of cameras to maximize the performance of these types of recognition tasks. Specifically, our goal is to optimize the quality of the joint observability of the tasks being performed by the subjects in an area. We develop a general analytical formulation of the observation problem, in terms of the statistics of the motion in the scene and the total resolution of the observed actions that is applicable to many observation tasks and multi-camera systems. A nonlinear optimization approach is used to find the internal and external (mounting position and orientation) camera parameters that optimize the recognition criteria. In these experiments, a single camera is repositioned using a mobile robot. Initial results for the problem of human activity recognition are presented.

The Scout is a miniature robot capable of performing surveillance and reconnaissance applications. However, the small size of the Scout limits the on-board processing capability and thus requires that the primary sensing modality (vision) be processed remotely. This creates a dependence upon a video channel which can become a severe bottleneck when attempting to use large numbers of robots. This paper discusses the newest generation of the Scout, the COTS 3.0, which attempts to reduce the effect of the communication bottleneck by using more local sensing capabilities to achieve a degree of autonomous functionality. Several experiments showing the durability of the new COTS Scout and the autonomous capability are presented.

When designing a mobile robotic team, an engineer is faced with many design choices. This paper discusses the design of a team consisting of two different models of robots with significantly different sensing and control capabilities intended to accomplish a similar task. Two new robotic platforms, the COTS Scout and the MegaScout are described along with their respective design considerations.

When a distributed robotic system is assigned to perform reconnaissance or surveillance, restrictions inherent to the design of an individual robot limit the system's performance in certain environments. Finding an ideal portable robotic platform capable of deploying and returning information in spatially restrictive areas is not a simple task. The Scout robot, developed at the University of Minnesota, is a viable robotic platform for these types of missions. The small form factor of the Scout allows for deployment, placement, and concealment of a team of robots equipped with a variety of sensory packages. However, the design of the Scout requires a compromise in power, sensor types, locomotion, and size; together these factors prevent an individual Scout from operating ideally in some environments. Several attempts to address these deficiencies have been implemented and are discussed. Among the prototype solutions are actuating wheels, allowing the Scout to increase ground clearance in varying terrains, a grappling hook enabling the Scout to obtain a position of elevated observation, and infrared emitters to facilitate low light operation.

Small scale distributed robotic systems are ideal for tasks that larger, more expensive robots may not be able to undertake such as surveillance or inspection in enclosed areas. Small scale robots also have the advantage of being easily portable to an area of interest. However, the advantages related to the small size and portability cause an increase in the complexity of development. In addition, the more pronounced effects of interacting with the environment in terms of mobility and communications lead to robotic systems of limited functionality. In order to address such deficiencies, several novel developments and improvements have been made to the Scout robot, which will be discussed. These improvements include the development of a communication relay system facilitating longer distance operation, an improved actuating wheel system increasing the Scout's mobility and a grappling hook system to elevate the Scout. By enhancing the Scout robotic team in this way, the functional use of the team is expanded, allowing more practical use.