Multisensor Fusion: A Minimal Representation Framework (Series In Intelligent Control And Intelligent Automation 11)

Multisensor Fusion: A Minimal Representation Framework (Series In Intelligent Control And Intelligent Automation 11)

By: Arthur C. Sanderson (author), Rajive Joshi (author)Hardback

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Description

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.

Contents

Introduction to multisensor integration; multisensor data fusion; multisensor fusion in object recognition; minimal representation; environment and sensor models; minimal representation multisensor fusion and model selection; multisensor fusion search algorithms; applying the abstract framework to concrete problems; multisensor object recognition in two dimensions; multisensor object recognition in three dimensions; laboratory experiments; discussion of experimental results.

Product Details

  • ISBN13: 9789810238803
  • Format: Hardback
  • Number Of Pages: 336
  • ID: 9789810238803
  • ISBN10: 9810238800

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