Advances in Unmanned Aerial Vehicles : State of the Art and the Road to Autonomy
There has been tremendous emphasis in unmanned aerial vehicles, both of fixed (airplanes) and rotary wing (vertical take off and landing, helicopters) types over the past ten years. Applications span both civilian and military domains, the latter being the most important at this stage. This edited book provides a solid and diversified reference source related to basic, applied research and development on small and miniature unmanned aerial vehicles, both fixed and rotary wing. As such, the book offers background information on the evolution of such vehicles over the years, followed by modeling and control fundamentals that are of paramount importance due to unmanned aerial vehicle model complexity, nonlinearity, coupling, inhirent instability and parameter values uncertainty. Aspects of navigation, including visual-based navigation and target tracking are discussed, followed by applications to attitude estimation on micro unmanned aerial vehicles, autonomous solar unmanned aerial vehicle, biomimetic sensing for autonomous flights in near-earth environments, localization of air-ground wireless sensor networks, decentralized formation tracking, design of an unmanned aerial vehicle for volcanic gas sampling and design of an on-board processing controller for miniature helicopters.
Advances in Probabilistic Graphical Models
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Advanced Motion Control and Sensing for Intelligent Vehicles
Provides the latest information in intelligent vehicle control, sensing, and intelligent transportation. It addresses the growing need for safe, comfortable, time and energy-efficient modes of transportation with emphasis on the latest key findings, current trends, and likely future developments in this rapidly expanding field. Highlights : Discusses individual vehicle dynamics, sensory and multiple ground-vehicle interactions / Includes systematic review of past and current research achievements / Presents case studies in cutting-edge directions such as vehicle steering motion, vehicle vision systems, cooperative driving, intersection safety, and tire pressure monitoring / Assesses the likely future developments of this field. This book is useful for both practicing engineers and researchers in the automotive industry.
Advanced Microsystems for Automotive Applications 2008 ; 4th ed.
With the total number of vehicles steadily increasing and soon approaching one billion, the world is facing serious challenges in terms of both safety of road transport and sustainability. Consequently the two major persistent issues for the automotive industry are improved safety and reduced emissions. The book in hand is a showroom of activities, the International Forum on Advanced Microsystems for Automotive Applications (AMAA) has been known for during the last 12 years.
Advanced Fuzzy Logic Technologies in Industrial Applications
Addresses the problem by introducing a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The tuning process is a major focus in this volume because it is the most difficult stage in fuzzy control application. Using new methods such as µ-law technique, histogram equalization and the Bezier-based method, all detailed here, the tuning process can be significantly simplified and control performance improved. The other great strength of this book lies in the range and contemporaneity of its applications and examples which include: laser tracking and control; robot calibration; image processing and pattern recognition; medical engineering; audio systems; autonomous underwater vehicles and data mining.
Adaptive Cooperation between Driver and Assistant System : Improving Road Safety
One of the next challenges in vehicular technology field is to improve drastically the road safety. Current developments are focusing on both vehicle platform and diverse assistance systems. This book presents a new engineering approach based on lean vehicle architecture ready for the drive-by-wire technology.
Activist Business Ethics
Examines international aspects, the personification of stakeholders, the predominance of values and ethics for CEOs and the inefficient safeguards of the stakeholders' interests. The book presents new vehicles for the safeguard of those interests, such as the Internet, Transparency, Ethical Funds and Activist Associations, and future activist vehicles, such as the Supervision Board and the Institute of Ethics.
3D-Position Tracking and Control for All-Terrain Robots
Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. This book demonstrates how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. In this work, a mechanical structure allowing smooth motion across obstacles with limited wheel slip is used. In particular, it enables the use of odometry and inertial sensors to improve the position estimation in rough terrain. A method for computing 3D motion increments based on the wheel encoders and chassis state sensors is developed. The algorithm runs online and can be adapted to any kind of passive wheeled rover. Finally, sensor fusion using 3D-Odometry, inertial sensors and visual motion estimation based on stereovision is presented. The experimental results demonstrate how each sensor contributes to increase the accuracy and robustness of the 3D position estimation.







