Teams of mobile robots have numerous applications, such as space exploration, underground mining, warehousing, and building security. Multi-robot teams can provide a number of practical benefits in such applications, including simultaneous presence in multiple locations, improved system performance, and greater robustness and redundancy compared to individual robots. This thesis addresses three aspects of coordination and navigation for teams of mobile robots: localization, the estimation of the position of each robot in the environment; motion planning, the process of finding collision-free trajectories through the environment; and task allocation, the selection of appropriate goals to be assigned to each robot. Each of these topics are investigated in the context of many robots working in a common environment. A particle-filter based system for cooperative global localization is presented. The system combines the sensor data from three robots, including measurements of the distances between robots, to cooperatively estimate the global position of each robot in the environment. The method is developed for a single triad of robots, then extended to larger groups of robots. The algorithm is demonstrated in a simulation of robots equipped with only simple range sensors, and is shown to successfully achieve global localization of robots that are unable to localize using only their own local sensor data. Motion planning is investigated for large teams of robots operating in tunnel and corridor environments, where coordinated planning is often required to avoid collision or deadlock conditions. A complete and scalable motion planning algorithm is presented and evaluated in simulation with up to 150 robots. In contrast to popular decoupled approaches to motion planning (which cannot guarantee a solution), this algorithm uses a multi-phase approach to create and maintain obstacle-free paths through a graph representation of the environment. The resulting plan is a set of collision-free trajectories, guaranteeing that every robot will reach its goal. The problem of task allocation is considered in the same type of tunnel and corridor environments, where tasks are defined as locations in the environment that must be visited by one of the robots in the team. To find efficient solutions to the task allocation problem, an optimization approach is used to generate potential task assignments, and select the best solution. The multi-phase motion planner is applied within this system as an efficient method of evaluating potential task assignments for many robots in a large environment. The algorithm is evaluated in simulations with up to 20 robots in a map of large underground mine. A real-world implementation of 3 physical robots was used to demonstrate the implementation of the multi-phase motion planning and task allocation systems. A centralized motion planning and task allocation system was developed, incorporating localization and time-dependent trajectory tracking on the robot processors, enabling cooperative navigation in a shared hallway environment.

The development of a new family of robotic vehicles for use in the exploration of Mars and other remote planets is an ongoing process. Current rovers have to traverse rough terrain and be able to withstand various conditions on Mars. The goal of this project is to design a new Mars rover mobility system that performs to optimum capability. This project will involve the design and control of a robot that will use wheels, as well as legs, allowing the robot to reconfigure itself to adapt to its current environment and traverse various terrains. This new reconfigurable hybrid robotic vehicle, Byrobot (named after the student), will have a six-legged mobility design for walking. Each leg will have 3 degrees of freedom, controlled by 3 separate servos, for the movement of the legs. Byrobot will also have 4 wheels each directly attached to the shaft of a DC motor, for four-wheel differential drive. By having these two mobility systems, Byrobot will be able to operate in various environments, by capitalizing on the advantages of both legged and wheeled robots. The CAD designing for this new robot is done on Pro-Engineer, and mechanisms and animations will be run to test movement of parts. The actual robot hardware will then be constructed in the Georgia Tech MRDC machine shop. The control system for the robot will be run by the Eyebot, which uses a 25MHz 32bit Controller (Motorola 68332), as well as the SSC-32 Servo Controller from Lynxmotion. This new robotic mobility platform will facilitate future Mars exploration.

With the growth of successes in pattern recognition and signal processing, mobile robot applications today are increasingly equipping their hardware with microphones to improve the set of available sensory information. However, if the robot, and therefore the microphone, ends up in a poor location acoustically, then the data will remain noisy and potentially useless for accomplishing the required task. This is compounded by the fact that there are many bad acoustic locations through which a robot is likely to pass, and so the results from auditory sensors often remain poor for much of the task. The movement of the robot, though, can also be an important tool for overcoming these problems, a tool that has not been exploited in the traditional signal processing community. Robots are not limited to a single location as are traditionally placed microphones, nor are they powerless over to where they will be moved as with wearable computers. If there is a better location available for performing its task, a robot can navigate to that location under its own power. Furthermore, when deciding where to move, robots can develop complex models of the environment. Using an array of sensors, a mobile robot can build models of sound flow through an area, picking from those models the paths most likely to improve performance of an acoustic application. In this dissertation, we address the question of how to exploit robotic movement. Using common sensors, we present a collection of tools for gathering information about the auditory scene and incorporating that information into a general framework for acoustical awareness. Thus equipped, robots can make intelligent decisions regarding control strategies to enhance their performance on the underlying acoustic application.

Many emerging controls applications have seen increased operational complexity due to the deployment of embedded, networked systems that must interact with the physical environment. In order to manage this complexity, we design different control modes for each system and use motion description languages (MDL) to specify a sequence of these controllers to execute at run-time. Unfortunately, current MDL frameworks lose some of the important details (i.e. power, spatial, or communication capabilities) that affect the execution of the control modes. This work presents several computational tools that work towards closing MDL's specification-to-execution gap, which can result in undesirable behavior of complex systems at run-time. First, we develop the notion of an MDL compiler for control specifications with spatial, energy, and temporal constraints. We define a new MDL for networked systems and develop an algorithm that automatically generates a supervisor to prevent incorrect execution of the multi-agent MDL program. Additionally, we derive conditions for checking if an MDL program satisfies actuator constraints and develop an algorithm to insert new control modes that maintain actuator bounds during the execution of the MDL program. Finally, we design and implement a software architecture that facilitates the development of control applications for systems with power, actuator, sensing, and communication constraints.

Our research focuses on one of the more fundamental issues in multi-agent, mobile robotics: the formation control problem. The idea is to create controllers that cause robots to move into a predefined formation shape. This is a well studied problem for the scenario in which the robots know in advance to which point in the formation they are assigned. In our case, we assume this information is not given in advance, but must be determined dynamically. This thesis presents an algorithm that can be used by a network of mobile robots to simultaneously determine efficient robot assignments and formation pose for rotationally and translationally invariant formations. This allows simultaneous role assignment and formation sysnthesis without the need for additional control laws. The thesis begins by introducing some general concepts regarding multi-agent robotics. Next, previous work and background information specific to the formation control and assignment problems are reviewed. Then the proposed assignment al- gorithm for role assignment and formation control is introduced and its theoretical properties are examined. This is followed by a discussion of simulation results. Lastly, experimental results are presented based on the implementation of the assignment al- gorithm on actual robots.

The objective of this thesis is to generate a discrete alphabet of low-level robotic controllers rich enough to mimic the actions of high-level users using the robot for a specific task. This alphabet will be built through the analysis of various user data sets in a modified version of the motion description language, MDLe. It can then be used to mimic the actions of a future user attempting to perform the task by calling scaled versions of the controls in the alphabet, potentially reducing the amount of data required to be transmitted to the robot, with minimal error. In this thesis, theory is developed that will allow the construction of such an alphabet, as well as its use to mimic new actions. A MATLAB algorithm is then built to implement the theory. This is followed by an experiment in which various users drive a Khepera robot through different courses with a joystick. The thesis concludes by presenting results which suggest that a relatively small group of users can generate an alphabet capable of mimicking the actions of other users, while drastically reducing bandwidth.

<p>This dissertation aims to present a structured overview of the state-of-the-art in cooperative robotics research. As we illustrate in this dissertation, there are several interesting aspects that draws attention to the field, among which 'Life Sciences' and 'Applied AI' are emphasized. We analyse the key concepts and main research issues within the field, and discuss its relations to other disciplines, including cognitive science, biology, artificial life and engineering. In particular it can be noted that the study of collective robot behaviour has drawn much inspiration from studies of animal behaviour. In this dissertation we also analyse one of the most attractive research areas within cooperative robotics today, namely RoboCup. Finally, we present a hierarchy of levels and mechanisms of cooperation in robots and animals, which we illustrate with examples and discussions.</p>

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<p>The major problem of robotics research today is that there is a barrier to entry into robotics research. Robot system software is complex and a researcher that wishes to concentrate on one particular problem often needs to learn about details, dependencies and intricacies of the complete system. This is because a robot system needs several different modules that need to communicate and execute in parallel.</p><p>Today there is not much controlled comparisons of algorithms and solutions for a given task, which is the standard scientific method of other sciences. There is also very little sharing between groups and projects, requiring code to be written from scratch over and over again.</p><p>This thesis proposes a general framework for robotics. By examining successful systems and architectures of past and present, yields a number of key properties. Some of these are ease of use, modularity, portability and efficiency. Even though there is much consensus on that the hybrid deliberate/reactive is the best architectural model that the community has produced so far, a framework should not stipulate a specific architecture. Instead the framework should enable the building of different architectures. Such a scheme implies that the modules are seen as common peers and not divided into clients and servers or forced into a set layering.</p><p>Using a standardized middleware such as CORBA, efficient communication can be carried out between different platforms and languages. Middleware also provides network transparency which is valuable in distributed systems. Component-based Software Engineering (CBSE) is an approach that could solve many of the aforementioned problems. It enforces modularity which helps to manage complexity. Components can be developed in isolation, since algorithms are encapsulated in components where only the interfaces need to be known by other users. A complete system can be created by assembling components from different sources.</p><p>Comparisons and sharing can greatly benefit from CBSE. A component-based framework called ORCA has been implemented with the following characteristics. All communication is carried out be either of three communication patterns, query, send and push. Communication is done using CORBA, although most of the CORBA code is hidden for the developer and can in the future be replaced by other mechanisms. Objects are transported between components in the form of the CORBA valuetype.</p><p>A component model is specified that among other things include support for a state-machine. This also handles initialization and sets up communication. Configuration is achieved by the presence of an XML-file per component. A hardware abstraction scheme is specified that basically route the communication patterns right down to the hardware level.</p><p>The framework has been verified by the implementation of a number of working systems. </p>

Thesis (Ph. D.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed January 13, 2009) Includes bibliographical references.