Mobile Robot Navigation with Intelligent Infrared Image 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 patter...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Fehlman, William L. (Συγγραφέας), Hinders, Mark K. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Springer London, 2009.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03524nam a22005055i 4500
001 978-1-84882-509-3
003 DE-He213
005 20151125161938.0
007 cr nn 008mamaa
008 100301s2009 xxk| s |||| 0|eng d
020 |a 9781848825093  |9 978-1-84882-509-3 
024 7 |a 10.1007/978-1-84882-509-3  |2 doi 
040 |d GrThAP 
050 4 |a TJ210.2-211.495 
050 4 |a T59.5 
072 7 |a TJFM1  |2 bicssc 
072 7 |a TEC037000  |2 bisacsh 
072 7 |a TEC004000  |2 bisacsh 
082 0 4 |a 629.892  |2 23 
100 1 |a Fehlman, William L.  |e author. 
245 1 0 |a Mobile Robot Navigation with Intelligent Infrared Image Interpretation  |h [electronic resource] /  |c by William L. Fehlman, Mark K. Hinders. 
264 1 |a London :  |b Springer London,  |c 2009. 
300 |a XXIX, 274 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a and Overview -- Data Acquisition -- Thermal Feature Generation -- Thermal Feature Selection -- Adaptive Bayesian Classification Model -- Conclusions and Future Research Directions. 
520 |a 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 robot’s 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), and makes direct use of prior knowledge regarding an object class’s existence in a robot’s immediate area of operation when making decisions regarding class assignments for unknown objects. The result is a novel classification model which not only displays exceptional performance in characterizing non-heat generating outdoor objects in thermal scenes, but also outperforms the traditional KNN and Parzen classifiers. Mobile Robot Navigation with Intelligent Infrared Image Interpretation will be of interest to researchers and developers of advanced mobile robots in academic, industrial and military sectors. Advanced undergraduates studying robot sensor interpretation, pattern classification or infrared physics will also appreciate this book. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Pattern recognition. 
650 0 |a Robotics. 
650 0 |a Automation. 
650 1 4 |a Engineering. 
650 2 4 |a Robotics and Automation. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Pattern Recognition. 
700 1 |a Hinders, Mark K.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781848825086 
856 4 0 |u http://dx.doi.org/10.1007/978-1-84882-509-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)