Collaborative perception, localization and mapping for autonomous systems / Yufeng Yue, Danwei Wang.
2021
TJ211.495
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Details
Title
Collaborative perception, localization and mapping for autonomous systems / Yufeng Yue, Danwei Wang.
ISBN
9789811588600 (electronic bk.)
9811588600 (electronic bk.)
9811588597
9789811588594
9811588600 (electronic bk.)
9811588597
9789811588594
Published
Singapore : Springer, [2021]
Language
English
Description
1 online resource (149 pages)
Item Number
10.1007/978-981-15-8860-0 doi
Call Number
TJ211.495
Dewey Decimal Classification
629.8/92
Summary
This book presents the breakthrough and cutting-edge progress for collaborative perception and mapping by proposing a novel framework of multimodal perception-relative localizationcollaborative mapping for collaborative robot systems. The organization of the book allows the readers to analyze, model and design collaborative perception technology for autonomous robots. It presents the basic foundation in the field of collaborative robot systems and the fundamental theory and technical guidelines for collaborative perception and mapping. The book significantly promotes the development of autonomous systems from individual intelligence to collaborative intelligence by providing extensive simulations and real experiments results in the different chapters. This book caters to engineers, graduate students and researchers in the fields of autonomous systems, robotics, computer vision and collaborative perception.
Bibliography, etc. Note
Includes bibliographical references.
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text file
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Description based on print version record.
Added Author
Wang, Danwei, Professor, author.
Series
Springer tracts in autonomous systems ; v. 2.
Available in Other Form
Collaborative Perception, Localization and Mapping for Autonomous Systems.
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Table of Contents
Introduction
Technical Background
Point Registration Approach for Map Fusion
Submap-Based Probabilistic Inconsistency Detection
Hierarchical Map Fusion Framework with Homogeneous Sensors
Collaborative 3D Mapping using Heterogeneous Sensors
All-Weather Collaborative Mapping with Dynamic Objects
Collaborative Probabilistic Semantic Mapping using CNN.
Technical Background
Point Registration Approach for Map Fusion
Submap-Based Probabilistic Inconsistency Detection
Hierarchical Map Fusion Framework with Homogeneous Sensors
Collaborative 3D Mapping using Heterogeneous Sensors
All-Weather Collaborative Mapping with Dynamic Objects
Collaborative Probabilistic Semantic Mapping using CNN.