Multisensor Data Fusion
Multisensor Data Fusion

Author: David Hall

Publisher: CRC Press

Published: 2001-06-20

Total Pages: 564

ISBN-13: 1420038540

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The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut

Multisensor Fusion
Multisensor Fusion

Author: Rajive Joshi

Publisher: World Scientific

Published: 1999

Total Pages: 340

ISBN-13: 9789810238803

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The fusion of information from sensors with different physical characteristics, such as sight, touch, sound, etc., enhances the understanding of our surroundings and provides the basis for planning, decision-making, and control of autonomous and intelligent machines. The minimal representation approach to multisensor fusion is based on the use of an information measure as a universal yardstick for fusion. Using models of sensor uncertainty, the representation size guides the integration of widely varying types of data and maximizes the information contributed to a consistent interpretation. In this book, the general theory of minimal representation multisensor fusion is developed and applied in a series of experimental studies of sensor-based robot manipulation. A novel application of differential evolutionary computation is introduced to achieve practical and effective solutions to this difficult computational problem.

Handbook of Multisensor Data Fusion
Handbook of Multisensor Data Fusion

Author: Martin Liggins II

Publisher: CRC Press

Published: 2017-01-06

Total Pages: 870

ISBN-13: 1351835378

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In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world’s leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field. New to the Second Edition— · Applications in electromagnetic systems and chemical and biological sensors · Army command and combat identification techniques · Techniques for automated reasoning · Advances in Kalman filtering · Fusion in a network centric environment · Service-oriented architecture concepts · Intelligent agents for improved decision making · Commercial off-the-shelf (COTS) software tools From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.

Multi-Hierarchical Representation of Large-Scale Space
Multi-Hierarchical Representation of Large-Scale Space

Author: Juan A. Fernández

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 284

ISBN-13: 9401596662

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It has been stated in psychology that human brain arranges information in a way that improves efficiency in performing common tasks, for example, information about our spatial environment is conveniently structured for efficient route finding. On the other hand, in computational sciences, the use of hierarchical information is well known for reducing the complexity of solving problems. This book studies hierarchical representations of large-scale space and presents a new model, called Multi-AH-graph, that uses multiple hierarchies of abstraction. It allows an agent to represent structural information acquired from the environment (elements such as objects, free space, etc., relations existing between them, such as proximity, similarity, etc. and other types of information, such as colors, shapes, etc). The Multi-AH-graph model extends a single hierarchy representation to a mUltiple hierarchy arrangement, which adapts better to a wider range of tasks, agents, and environments. We also present a system called CLAUDIA, which is an implementation of the task-driven paradigm for automatic construction of multiple abstractions: a set of hierarchies of abstraction will be "good" for an agent if it can reduce the cost of planning and performing certain tasks of the agent in the agent's world. CLAUDIA constructs multiple hierarchies (Multi-AH-graphs) for a given triple , trying to optimize their "goodness".

Control in Robotics and Automation
Control in Robotics and Automation

Author: Bijoy K. Ghosh

Publisher: Elsevier

Published: 1999-04-09

Total Pages: 442

ISBN-13: 0080503071

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Microcomputer technology and micromechanical design have contributed to recent rapid advances in Robotics. Particular advances have been made in sensor technology that allow robotic systems to gather data and react "intelligently" in flexible manufacturing systems. The analysis and recording of the data are vital to controlling the robot.In order to solve problems in control and planning for a Robotic system it is necessary to meet the growing need for the integration of sensors in to the system. Control in Robotics and Automation addresses this need. This book covers integration planning and control based on prior knowledge and real-time sensory information. A new task-oriented approach to sensing, planning and control introduces an event-based method for system design together with task planning and three dimensional modeling in the execution of remote operations.Typical remote systems are teleoperated and provide work efficiencies that are on the order of ten times slower than what is directly achievable by humans. Consequently, the effective integration of automation into teleoperated remote systems offers potential to improve remote system work efficiency. The authors introduce visually guided control systems and study the role of computer vision in autonomously guiding a robot system. - Sensor-Based Planning and Control in an Event-Based Approach - Visually Guided Sensing and Control - Multiple Sensor Fuson in Planning and Control - System Integration and Implementation - Practical Applications

Artificial Intelligence in Real-Time Control 1989
Artificial Intelligence in Real-Time Control 1989

Author: Hua-Tian Li

Publisher: Elsevier

Published: 2014-07-04

Total Pages: 127

ISBN-13: 1483298337

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Papers presented at the workshop are representative of the state-of-the art of artificial intelligence in real-time control. The issues covered included the use of AI methods in the design, implementation, testing, maintenance and operation of real-time control systems. While the focus was on the fundamental aspects of the methodologies and technologies, there were some applications papers which helped to put emerging theories into perspective. The four main subjects were architectural issues; knowledge - acquisition and learning; techniques; and scheduling, monitoring and management.

Exploratory Vision
Exploratory Vision

Author: Michael S. Landy

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 351

ISBN-13: 1461239842

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Advances in sensing, signal processing, and computer technology during the past half century have stimulated numerous attempts to design general-purpose ma chines that see. These attempts have met with at best modest success and more typically outright failure. The difficulties encountered in building working com puter vision systems based on state-of-the-art techniques came as a surprise. Perhaps the most frustrating aspect of the problem is that machine vision sys tems cannot deal with numerous visual tasks that humans perform rapidly and effortlessly. In reaction to this perceived discrepancy in performance, various researchers (notably Marr, 1982) suggested that the design of machine-vision systems should be based on principles drawn from the study of biological systems. This "neuro morphic" or "anthropomorphic" approach has proven fruitful: the use of pyramid (multiresolution) image representation methods in image compression is one ex ample of a successful application based on principles primarily derived from the study of biological vision systems. It is still the case, however, that the perfor of computer vision systems falls far short of that of the natural systems mance they are intended to mimic, suggesting that it is time to look even more closely at the remaining differences between artificial and biological vision systems.

Multisensor Integration and Fusion for Intelligent Machines and Systems
Multisensor Integration and Fusion for Intelligent Machines and Systems

Author: Ren C. Luo

Publisher: Intellect Books

Published: 1995

Total Pages: 736

ISBN-13:

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There has been a growing interest during the 1990s in the use of multiple sensors to increase the capabilities of intelligent machines and systems. This text is a compendium of some of the most important and influential work that has appeared in this area. In addition, it contains comprehensive introductory material and an extensive survey and review of related research. The volume should be useful to everyone interested in the development of more intelligent machines and systems through the synergistic use of multiple sensors.