Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment - Xiaochun Wang, Xiali Wang, Don Mitchell Wilkes

Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment

Buch | Softcover
328 Seiten
2020 | 1st ed. 2020
Springer Verlag, Singapore
978-981-13-9219-1 (ISBN)
106,99 inkl. MwSt
This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.

Xiaochun Wang received her BS degree from Beijing University and the PhD degree from the Department of Electrical Engineering and Computer Science, Vanderbilt University. She is currently an associate professor of School of Software Engineering at Xi’an Jiaotong University. Her research interests are in computer vision, signal processing, and pattern recognition. Xia Li Wang received the PhD degree from the Department of Computer Science, Northwest University, China, in 2005. He is a faculty member in the Department of Computer Science, Changan University, China. His research interests are in computer vision, signal processing, intelligent traffic system, and pattern recognition. D. Mitchell Wilkes received the BSEE degree from Florida Atlantic, and the MSEE and PhD degrees from Georgia Institute of Technology. His research interests include digital signal processing, image processing and computer vision, structurally adaptive systems, sonar,as well as signal modeling. He is a member of the IEEE and a faculty member at the Department of Electrical Engineering and Computer Science, Vanderbilt University. He is a member of the IEEE.

Part I Introduction.- Part II Unsupervised Learning.- Part III Supervised Learning and Semi-Supervised Learning.- Part IV Reinforcement Learning.

Erscheinungsdatum
Zusatzinfo 78 Illustrations, color; 21 Illustrations, black and white; XXII, 328 p. 99 illus., 78 illus. in color.
Verlagsort Singapore
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Elektrotechnik / Energietechnik
Technik Maschinenbau
Schlagworte Autonomous Mobile Robot Localization • Computer Vision and Machine Perception • Hippocampal Configural Represenations • machine learning methodologies • Natural Scene Recognition in An Unknown Environment • Prefrontal Cortex Working Memory System
ISBN-10 981-13-9219-6 / 9811392196
ISBN-13 978-981-13-9219-1 / 9789811392191
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
alles zum Drucken, Scannen, Modellieren

von Werner Sommer; Andreas Schlenker

Buch | Softcover (2024)
Markt + Technik Verlag
24,95
Einstieg und Praxis

von Werner Sommer; Andreas Schlenker

Buch | Softcover (2023)
Markt + Technik (Verlag)
19,95