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Multisensor Fusion: A Minimal Representation Framework (Series in Intelligent Control and Intelligent Automation, Volume 11)
 
 
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Multisensor Fusion: A Minimal Representation Framework (Series in Intelligent Control and Intelligent Automation, Volume 11) [Hardcover]

Rajive Joshi (Author), Arthur C. Sanderson (Author)

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Book Description

June 2000 9810238800 978-9810238803
The fusion of information from sensors with different physical characteristics, such as sights, touch and sound, 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 work, a 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.

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Inside This Book (learn more)
First Sentence:
Sensory data processing and interpretation is a very basic characteristic of intelligent beingsone that empowers them to interact with their environment. Read the first page
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Computing Two-Dimensional Pose, Experiment Id Sensor, Model Feature Count, Modeled Axis Error, Size Deviation Ref, Translation Error Rep, Unmodeled Spurious
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