Overview of Consensus Algorithms in Cooperative Control -- Overview of Consensus Algorithms in Cooperative Control -- Consensus Algorithms for Single-integrator Dynamics -- Consensus Algorithms for Single-integrator Dynamics -- Consensus Tracking with a Reference State -- Consensus Algorithms for Double-integrator Dynamics -- Consensus Algorithms for Double-integrator Dynamics -- Extensions to a Reference Model -- Consensus Algorithms for Rigid Body Attitude Dynamics -- Consensus Algorithms for Rigid Body Attitude Dynamics -- Relative Attitude Maintenance and Reference Attitude Tracking -- Consensus-based Design Methodologies for Distributed Multivehicle Cooperative Control -- Consensus-based Design Methodologies for Distributed Multivehicle Cooperative Control -- Applications to Multivehicle Cooperative Control -- Rendezvous and Axial Alignment with Multiple Wheeled Mobile Robots -- Distributed Formation Control of Multiple Wheeled Mobile Robots with a Virtual Leader -- Decentralized Behavioral Approach to Wheeled Mobile Robot Formation Maneuvers -- Deep Space Spacecraft Formation Flying -- Cooperative Fire Monitoring with Multiple UAVs -- Cooperative Surveillance with Multiple UAVs.

The coordinated use of autonomous vehicles has an abundance of potential applications from the domestic to the hazardously toxic. Frequently the communications necessary for the productive interplay of such vehicles may be subject to limitations in range, bandwidth, noise and other causes of unreliability. Information consensus guarantees that vehicles sharing information over a network topology have a consistent view of information critical to the coordination task. Assuming only neighbor-neighbor interaction between vehicles, Distributed Consensus in Multi-vehicle Cooperative Control develops distributed consensus strategies designed to ensure that the information states of all vehicles in a network converge to a common value. This approach strengthens the team, minimizing power consumption and the deleterious effects of range and other restrictions. The monograph is divided into six parts covering introductory, theoretical and experimental material and featuring: • an overview of the use of consensus algorithms in cooperative control; • consensus algorithms in single- and double-integrator dynamical systems; • consensus algorithms for rigid-body attitude dynamics; • rendezvous and axial alignment, formation control, deep-space formation flying, fire monitoring and surveillance. Notation drawn from graph and matrix theory and background material on linear and nonlinear system theory are enumerated in six appendices. The authors maintain a website at which can be found a sample simulation and experimental video material associated with experiments in several chapters of this book. Academic control systems researchers and their counterparts in government laboratories and robotics- and aerospace-related industries will find the ideas presented in Distributed Consensus in Multi-vehicle Cooperative Control of great interest. This text will also serve as a valuable support and reference for graduate courses in robotics, and linear and nonlinear control systems.