Localization and Mapping of Autonomous Mobile Robots
eBook - ePub

Localization and Mapping of Autonomous Mobile Robots

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Localization and Mapping of Autonomous Mobile Robots

About this book

Localization and mapping play a critical role in the autonomous task execution of mobile robots. This book covers the theoretical and technological aspects of robot localization and mapping, including visual localization and mapping, visual relocalization, LiDAR localization and mapping, and place recognition.

It provides the theoretical foundations of robot localization and mapping. It employs both traditional methods, such as geometry-based visual localization, and state-of-the-art deep learning techniques that improve robot perception. The authors also address LiDAR-based localization, exploring techniques to improve both efficiency and accuracy when processing dense point clouds. Key topics include visual localization using deep features, integration of visual solutions under ROS-based software architecture, and distribution-based LiDAR localization.

This book will be of great interest to students and professionals in the fields of robotics and artificial intelligence. It will also be an excellent reference for engineers and technicians involved in the development of robot localization.

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Yes, you can access Localization and Mapping of Autonomous Mobile Robots by Junzhi Yu,Zhiqiang Cao,Peiyu Guan,Chengpeng Wang in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. List of Figures and Tables
  7. Chapter 1 ◾ Introduction
  8. Chapter 2 ◾ Mathematical Foundation of Localization and Mapping Theory
  9. Chapter 3 ◾ Real-Time Semantic Visual SLAM with Points and Objects
  10. Chapter 4 ◾ Visual Relocalization from the Perspective of Scene Coordinate Regression Network
  11. Chapter 5 ◾ Visual Relocalization from the Perspective of Place Recognition
  12. Chapter 6 ◾ Robot Visual Localization Framework Based on Offline Hybrid Map
  13. Chapter 7 ◾ Hierarchical LiDAR Odometry via Maximum Likelihood Estimation with Tightly Associated Distributions
  14. Chapter 8 ◾ Hierarchical Distribution-Based Tightly Coupled LiDAR Inertial Odometry
  15. Chapter 9 ◾ LiDAR Place Recognition Based on Range Image and Column-Shift-Invariant Attention
  16. Chapter 10 ◾ Summary and Outlook
  17. Index