Machine Learning-Based Natural Scene Recognition for Mobile Robot Localization in an Unknown Environment

By Xiaochun Wang and Don Mitchell Wilkes

Book Overview

Part I Introduction1 Overview and Contributions2 Developments in Mobile Robot Localization Research3 A Computer Vision System for Visual Perception in Unknown Environments

Part II Unsupervised Learning4 Theory: Clustering5 Algorithm I: A Fast Approximate EMST Algorithm for High-Dimensional Image Data6 Algorithm II: An Efficient K-medoids Clustering Algorithm for Large Scale Image Data7 Algorithm III: Enhancing Complete Linkage Clustering via Boundary Point Detection8 Algorithm IV: A New Fast k-Nearest Neighbor-Based Clustering Algorithm
Part III Supervised Learning and Semi-Supervised Learning9 Theory: K-nearest Neighbor Classifiers10 Application I: A Fast Image Retrieval Method Based on Quantization Tree
11 Application II: A Fast Incremental Spectral Clustering Algorithm for Image Segmentation

Part IV Reinforcement Learning12 Theory: Human-Like Localization Inspired by a Hippocampal Memory Mechanism13 Application I: A Developmental Robotic Paradigm Using Working Memory Learning Mechanism14 Application II: An Autonomous Vision System Based Sensor-Motor Coordination for Open Space Detection15 Application III: Visual Percepts Learning for Mobile Robot Localization in An Indoor Environment16 Application IV: An Automatic Natural Scene Recognition Method for Mobile Robot Localization in An Outdoor Environment

• Format: Paperback
• Language: English
• ISBN: 9811392196
• ISBN13: 9789811392191
• Release Date: August 2020
• Publisher: Springer
• Length: 328 Pages
• Weight: 1.09 lbs.
• Dimensions: 0.7" x 6.1" x 9.2"