Robotics is an important part of modern engineering involving electricity and electronics, computers, mathematics, and mechanism design. In recent years, in addition to serial robots, multi-robot systems have begun to attract the attention of students, academics, and industry workers. This interest has directly impacted the development of novel theoretical research areas and products. This book explores new developments in multi-robot systems, such as trajectory planning, control algorithms, and programming.

In March 2002, the Naval Research Laboratory brought together leading researchers and government sponsors for a three-day workshop in Washington, D.C. on Multi-Robot Systems. The workshop began with presentations by various government program managers describing application areas and programs with an interest in multi robot systems. Government representatives were on hand from the Office of Naval Research, the Air Force, the Army Research Lab, the National Aeronau tics and Space Administration, and the Defense Advanced Research Projects Agency. Top researchers then presented their current activities in the areas of multi robot systems and human-robot interaction. The first two days of the workshop of1ocalizatio~. concentrated on multi-robot control issues, including the topics mapping, and navigation; distributed surveillance; manipulation; coordination and formations; and sensors and hardware. The third day was focused on hu man interactions with multi-robot teams. All presentations were given in a single-track workshop format. This proceedings documents the work presented by these researchers at the workshop. The invited presentations were followed by panel discussions, in which all participants interacted to highlight the challenges of this field and to develop possible solutions. In addition to the invited research talks, students were given an opportunity to present their work at poster sessions.

Offers a theoretical and practical guide to the communication and navigation of autonomous mobile robots and multi-robot systems This book covers the methods and algorithms for the navigation, motion planning, and control of mobile robots acting individually and in groups. It addresses methods of positioning in global and local coordinates systems, off-line and on-line path-planning, sensing and sensors fusion, algorithms of obstacle avoidance, swarming techniques and cooperative behavior. The book includes ready-to-use algorithms, numerical examples and simulations, which can be directly implemented in both simple and advanced mobile robots, and is accompanied by a website hosting codes, videos, and PowerPoint slides Autonomous Mobile Robots and Multi-Robot Systems: Motion-Planning, Communication and Swarming consists of four main parts. The first looks at the models and algorithms of navigation and motion planning in global coordinates systems with complete information about the robot’s location and velocity. The second part considers the motion of the robots in the potential field, which is defined by the environmental states of the robot's expectations and knowledge. The robot's motion in the unknown environments and the corresponding tasks of environment mapping using sensed information is covered in the third part. The fourth part deals with the multi-robot systems and swarm dynamics in two and three dimensions. Provides a self-contained, theoretical guide to understanding mobile robot control and navigation Features implementable algorithms, numerical examples, and simulations Includes coverage of models of motion in global and local coordinates systems with and without direct communication between the robots Supplemented by a companion website offering codes, videos, and PowerPoint slides Autonomous Mobile Robots and Multi-Robot Systems: Motion-Planning, Communication and Swarming is an excellent tool for researchers, lecturers, senior undergraduate and graduate students, and engineers dealing with mobile robots and related issues.

This proceedings volume documents recent cutting-edge developments in multi-robot systems research. This volume is the result of the Third International workshop on Multi-Robot Systems that was held in March 2005 at the Naval Research Laboratory in Washington, D.C. This workshop brought together top researchers working in areas relevant to designing teams of autonomous vehicles, including robots and unmanned ground, air, surface, and undersea vehicles. The workshop focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. A broad range of applications of this technology are presented in this volume, including UCAVS (Unmanned Combat Air Vehicles), micro-air vehicles, UUVs (Unmanned Underwater Vehicles), UGVs (Unmanned Ground vehicles), planetary exploration, assembly in space, clean-up, and urban search and rescue. This proceedings volume represents the contributions of the top researchers in this field and serves as a valuable tool for professionals in this interdisciplinary field.

This monograph introduces novel responses to the different problems that arise when multiple robots need to execute a task in cooperation, each robot in the team having a monocular camera as its primary input sensor. Its central proposition is that a consistent perception of the world is crucial for the good development of any multi-robot application. The text focuses on the high-level problem of cooperative perception by a multi-robot system: the idea that, depending on what each robot sees and its current situation, it will need to communicate these things to its fellows whenever possible to share what it has found and keep updated by them in its turn. However, in any realistic scenario, distributed solutions to this problem are not trivial and need to be addressed from as many angles as possible. Distributed Consensus with Visual Perception in Multi-Robot Systems covers a variety of related topics such as: • distributed consensus algorithms; • data association and robustness problems; • convergence speed; and • cooperative mapping. The book first puts forward algorithmic solutions to these problems and then supports them with empirical validations working with real images. It provides the reader with a deeper understanding of the problems associated to the perception of the world by a team of cooperating robots with onboard cameras. Academic researchers and graduate students working with multi-robot systems, or investigating problems of distributed control or computer vision and cooperative perception will find this book of material assistance with their studies.

The trend in the evolution of robotic systems is that the number of degrees of freedom increases. This is visible both in robot manipulator design and in the shift of focus from single to multi-robot systems. Following the principles of evolution in nature, one may infer that adding degrees of freedom to robot systems design is beneficial. However, since nature did not select snake-like bodies for all creatures, it is reasonable to expect the presence of a certain selection pressure on the number of degrees of freedom. Thus, understanding costs and benefits of multiple degrees of freedom, especially those that create redundancy, is a fundamental problem in the field of robotics. This volume is mostly based on the works presented at the workshop on Redundancy in Robot Manipulators and Multi-Robot Systems at the IEEE/RSJ International Conference on Intelligent Robots and Systems - IROS 2011. The workshop was envisioned as a dialog between researchers from two separate, but obviously related fields of robotics: one that deals with systems having multiple degrees of freedom, including redundant robot manipulators, and the other that deals with multirobot systems. The volume consists of twelve chapters, each representing one of the two fields.

Obstacle Avoidance in Multi-robot Systems: Experiments in Parallel Genetic Algorithms offers a novel framework for solving the path planning problem for robot manipulators. Simple and efficient solutions are proposed for the path planning problem based on genetic algorithms. One of the attractive features of genetic algorithms is their ability to solve formidable problems in a robust and straightforward manner. Moreover, genetic algorithms are inherently parallel in nature, which makes them ideal candidates for parallel computing implementations.By combining the robustness of genetic algorithms with the power of parallel computers, this book provides an effective and practical approach to solving path planning problems. The book gives details of implementations that allow a better understanding of the complexities involved in the development of parallel path planning algorithms. The material presented is interdisciplinary in nature ? it combines topics from robotics, genetic algorithms, and parallel processing. The book can be used by practitioners and researchers in computer science and engineering.

Great interest is now focused on distributed autonomous robotic systems (DARS) as a new strategy for the realization of flexible, robust, and intelligent robots. Inspired by autonomous, decentralized, and self-organizing biological systems, the field of DARS encompasses broad interdisciplinary technologies related not only to robotics and computer engineering but also to biology and psychology. The rapidly growing interest in this new area of research was manifest in the first volume of Distributed Autonomous Robotic Systems, published in 1994. This second volume in the series presents the most recent work by eminent researchers and includes such topics as multirobot control, distributed robotic systems design, self-organizing systems, and sensing and navigation for cooperative robots. Distributed Autonomous Robotic Systems 2 is a valuable source for those whose work involves robotics and will be of great interest to those in the fields of artificial intelligence, self-organizing systems, artificial life, and computer science.

As a new strategy to realize the goal of flexible, robust, fault-tolerant robotic systems, the distributed autonomous approach has quickly established itself as one of the fastest growing fields in robotics. This book is one of the first to devote itself solely to this exciting area of research, covering such topics as self-organization, communication and coordination, multi-robot manipulation and control, distributed system design, distributed sensing, intelligent manufacturing systems, and group behavior. The fundamental technologies and system architectures of distributed autonomous robotic systems are expounded in detail, along with the latest research findings. This book should prove indispensable not only to those involved with robotic engineering but also to those in the fields of artificial intelligence, self-organizing systems, and coordinated control.

In this dissertation, methods for optimal multi-robot task allocation (MRTA) for industrial plant inspection are investigated. MRTA involves distributing and scheduling a set of tasks for a group of robots to minimize the total cost taking into account operational constraints. With technical progress and declining cost of robotic mobility, interest in industrial mobile robotics has grown significantly in recent years. Many efforts have been devoted to mobility-related problems such as self-localization and mapping, though only few studies deal with the optimal task allocation in multi-robot systems. Since a good task allocation provides more efficient scheduling (e.g. less cost, shorter time), the objective of this research is to develop search/optimization methods for inspection problems that involve both single- and two-robot tasks.