Robot Systems for Rail Transit Applications
1st Edition
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Description
Robot Systems for Rail Transit Applications presents the latest advances in robotics and artificial intelligence for railway systems, giving foundational principles and running through special problems in robot systems for rail transit. State-of-the art research in robotics and railway systems is presented alongside a series of real-world examples. Eight chapters give definitions and characteristics of rail transit robot systems, describe assembly and collaborative robots in manufacturing, introduce automated guided vehicles and autonomous rail rapid transit, demonstrate inspection robots, cover trench robots, and explain unmanned aerial vehicles. This book offers an integrated and highly-practical way to approach robotics and artificial intelligence in rail-transit.
Key Features
- Introduces robot and artificial intelligence (AI) systems for rail transit applications
- Presents research alongside step-by-step coverage of real-world cases
- Gives the theoretical foundations underlying practical application
- Offers solutions for high-speed railways from the latest work in robotics
- Shows how robotics and AI systems afford new and efficient methods in rail transit
Readership
Researchers and graduate students in transportation engineering and applied robotics; engineers in applied robot systems and rail transit
Table of Contents
Chapter 1: Introduction
1.1 Overview of the rail transit robot systems
1.2 Fundamental key problems of the rail transit robot systems
1.2.1 Navigation and trajectory planning
1.2.2 Human-machine interaction
1.2.3 Power management
1.3 Scope of this book
1.4 References
Chapter 2: Rail transit assembly robot systems
2.1 Overview of the rail transit assembly robot systems
2.2 Hardware structures of the rail transit assembly robots
2.3 Arm dynamics of the rail transit assembly robots
2.3.1 Description of the arm postures
2.3.2 Forward dynamics theory
2.3.3 Inverse dynamics theory
2.3.4 Trajectory planning of the robot arms
2.4 Inverse dynamic computation based on artificial neural networks
2.5 References
Chapter 3: Rail transit collaborative robot systems
3.1 Overview of the rail transit collaborative robot systems
3.2 Hardware structures of the rail transit collaborative robots
3.3 Visual perceptions of the rail transit collaborative robots
3.3.1 Feature extraction algorithms
3.3.2 Target detection of the rail transit collaborative robots
3.3.3 Target tracking of the rail transit collaborative robots
3.4 References
Chapter 4: Automatic Guided Vehicles (AGV) in rail transit intelligent manufacturing environment
4.1 Overview of the AGV in intelligent manufacturing environment
4.2 Hardware structure of the AGV in intelligent manufacturing environment
4.3 AGV systems
4.3.1 Navigation methods of the AGV
4.3.2 Route-planning algorithms of the AGV
4.3.3 Human-robot interaction in the rail transit manufacturing environment
4.3.4 Tasks assignments of the AGV systems
4.4 Hybrid model based AGV route-planning in the rail transit manufacturing environment
4.5 References
Chapter 5 Autonomous Rail Rapid Transit (ART)
5.1 Overview of the ART
5.2 Hardware structure of the ART
5.3 ART systems
5.3.1 Road traffic interaction systems of the ART
5.3.2 Navigation systems of the ART
5.3.3 Communication Systems of the ART
5.3.4 Scheduling management systems of the ART
5.4 Pedestrian detection algorithms for the intelligent driving
5.5 References
Chapter 6 Rail transit inspection robots
6.1 Overview of the rail transit inspection robots
6.2 Hardware structures of the rail transit inspection robots
6.3 Rail transit inspection robot systems
6.3.1 Positioning and navigation methods of the rail transit inspection robots
6.3.2 Path planning algorithms of the rail transit inspection robots
6.3.3 Hand eye vision systems of the rail transit inspection robots
6.4 References
Chapter 7 Rail transit channel robot systems
7.1 Overview of rail transit channel robot systems
7.2 Hardware structures of the rail transit channel robots
7.3 Channel robot TEDS intelligent sensing systems
7.4 Bogie fault diagnosis based on deep learning models
7.5 References
Chapter 8 Rail Transit Inspection Unmanned Aerial Vehicle (UAV)
8.1 Overview of rail transit inspection UAV
8.2 Hardware structures of the rail traffic inspection UAV
8.3. Rail transit inspection UAV systems
8.3.1 Communication systems of the rail transit inspection UAV
8.3.2 Data collection systems of the rail transit inspection UAV
8.3.3 Scheduling systems of the rail transit inspection UAV
8.4 Rail transit Intruding detection based on the inspection UAV
8.5 References
Details
- No. of pages:
- 418
- Language:
- English
- Copyright:
- © Elsevier 2020
- Published:
- 29th June 2020
- Imprint:
- Elsevier
- Paperback ISBN:
- 9780128229682
- eBook ISBN:
- 9780128229408
About the Author
Hui Liu
Hui Liu is a Professor of Robotics and Artificial Intelligence, at Central South University, China, as well as a Vice Dean of the Faculty of Traffic and Transportation Engineering, and Director of the Institute of Artificial Intelligence and Robotics (IAIR). He received a Ph.D. in Automation Engineering, and his habilitation, from Rostock University in Germany. He has published more than 70 papers, and holds over 50 patents.
Affiliations and Expertise
Central South University, in Changsha, China
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