Mobile Robot Navigation with Intelligent Infrared Image Interpretation [Paperback]

Mobile robots require the ability to make decisions such as go through the hedges or go around the brick wall. Mobile Robot Navigation with Intelligent Infrared Image Interpretation describes in detail an alternative to GPS navigation: a physics-based adaptive Bayesian pattern classification model that uses a passive thermal infrared imaging system to automatically characterize non-heat generating objects in unstructured outdoor environments for mobile robots. The resulting classification model complements an autonomous robots situational awareness by providing the ability to classify smaller structures commonly found in the immediate operational environment.

This book details an alternative to GPS navigation for mobile robots, a model that allows them to use infrared imaging to assess the physical nature of surrounding structures. Thus, the robots can make navigational decisions without human interpretation.

Mobile robots require the ability to make decisions such as go through the hedges or go around the brick wall. Mobile Robot Navigation with Intelligent Infrared Image Interpretation describes in detail an alternative to GPS navigation: a physics-based adaptive Bayesian pattern classification model that uses a passive thermal infrared imaging system to automatically characterize non-heat generating objects in unstructured outdoor environments for mobile robots. The resulting classification model complements an autonomous robots situational awareness by providing the ability to classify smaller structures commonly found in the immediate operational environment.

The approach described in this book is an application of Bayesian statistical pattern classification where learning involves labeled classes of data (supervised classification), assumes no formal structure regarding the density of the data in the classes (nonparametric density estimation), andlCo