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Introduction to Intelligent ­Robot System Design
Application Development with Ros

Rating
Format
Hardback, 777 pages
Other Formats Available

Paperback : HK$640.00

Published
Singapore, 1 September 2023

Chapter 1:The Composition of Typical Robot System


1.1 Mechanical Composition of Robot System


1.2 Hardware Composition of Robot System

1.3 Sensor Description and Function Introduction


1.4 End-effecter of Robot System


1.5 Software Composition of Robot System

First Task: Move Robot: Start Using the Robot Platform with Demo



Chapter 2:Connect the Robot to ROS


2.1 Getting Started with ROS


2.2 How to Install ROS


2.2 ROS Architecture and Communication Foundation


2.3 Program the first ROS Demo


First Task: Run a Simple ROS Demo


Second Task: Run the Turtle


2.4 Introduction to ROS Common Components

2.5 Implementation Process of Hello Spark


Third Task: Run the Spark


2.6 Introduction to ROS External Device



Chapter 3:Preliminary Construction of Robot System Model


3.1 Start with the Mobile Robot


First Task: Synchronized Movement between ROS Simulation and Real Robot


3.2 Understanding Lidar


3.3 Data Processing of Lidar in ROS: Data Processing of Point Cloud


Second Task: Observe the Environment in Robotic Perspective: Point Cloud of Moving Car



Chapter 4:Laser SLAM


4.1 Theoretical Basis of SLAM


First Task: Gazebo and ROS Integration Environment Preparation

4.2 Fundamental of SLAM


4.3 Environmental Mapping


Second Task: Introduction to Compile and Install "cartograoher" and Precautions


4.4 Realization of Closed-loop Behavior

Third Task: Control the car to complete the indoor mapping



Chapter 5: Autonomous Navigation


5.1 Map-based positioning


First Task: Mobile robot positioning


5.2 Map-based Autonomous Navigation


Second Task: Mobile Robot Navigation



Chapter 6: SLAM Based on Multiple Sensors


6.1 IMU Model and Calibration


6.2 Odometer


6.3 Data Fusion Based on Kalman Filter


First Task: SLAM Practice of Multi-sensor Fusion



Chapter 7: Robotic Arm Motion Control


7.1 Robotic Arm


7.2 Robotic Arm Control:MoveIt!


First Task: Move the Robotic Arm:MoveIt! and Gazebo Simulation



Chapter 8: Machine Vision


8.1 Understanding OpenCV


8.2 Use the Monocular Vision Sensor


First Task: Install Monocular Camera Driver


8.3 Camera Calibration


8.4 Image Processing Based on Vision Sensor


8.5 Target Recognition Based on OpenCV


Second Task: Identify Objects



Chapter 9: Object Grasping with Vision-based Robotic Arm

9.1 Use the Depth Camera


First Task: Install Depth Camera Driver


9.2 Perceive:Object Recognition Based on Depth Camera


Second Task: Object Recognition based on Convolutional Neural Network


9.3 Hand-eye Calibration


Third Task: Use the "easy_handeye" Function Package


9.4 Plan:Grasp gesture generation


Fourth Task: Robotic Arm Grasp Objects



Chapter 10:Vision-based Mobile Robot


10.1 Vision-based Object Recognition and Positioning


10.2 Visual Servoing of Mobile Robots


First Task: Move Robotic Arm to Grasp Objects



Chapter 11:Visual SLAM and 3D Reconstruction


11.1 Framework of Classic Visual SLAM


First Task: Use rtab_map for 3D Positioning and Mapping


11.2 ORB-SLAM2 Algorithm


11.3 VINS-Fusion Algorithm


11.4 3D Reconstruction Based On Dense SLAM


Second Task: Use Depth Camera for Navigation


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Product Description

Chapter 1:The Composition of Typical Robot System


1.1 Mechanical Composition of Robot System


1.2 Hardware Composition of Robot System

1.3 Sensor Description and Function Introduction


1.4 End-effecter of Robot System


1.5 Software Composition of Robot System

First Task: Move Robot: Start Using the Robot Platform with Demo



Chapter 2:Connect the Robot to ROS


2.1 Getting Started with ROS


2.2 How to Install ROS


2.2 ROS Architecture and Communication Foundation


2.3 Program the first ROS Demo


First Task: Run a Simple ROS Demo


Second Task: Run the Turtle


2.4 Introduction to ROS Common Components

2.5 Implementation Process of Hello Spark


Third Task: Run the Spark


2.6 Introduction to ROS External Device



Chapter 3:Preliminary Construction of Robot System Model


3.1 Start with the Mobile Robot


First Task: Synchronized Movement between ROS Simulation and Real Robot


3.2 Understanding Lidar


3.3 Data Processing of Lidar in ROS: Data Processing of Point Cloud


Second Task: Observe the Environment in Robotic Perspective: Point Cloud of Moving Car



Chapter 4:Laser SLAM


4.1 Theoretical Basis of SLAM


First Task: Gazebo and ROS Integration Environment Preparation

4.2 Fundamental of SLAM


4.3 Environmental Mapping


Second Task: Introduction to Compile and Install "cartograoher" and Precautions


4.4 Realization of Closed-loop Behavior

Third Task: Control the car to complete the indoor mapping



Chapter 5: Autonomous Navigation


5.1 Map-based positioning


First Task: Mobile robot positioning


5.2 Map-based Autonomous Navigation


Second Task: Mobile Robot Navigation



Chapter 6: SLAM Based on Multiple Sensors


6.1 IMU Model and Calibration


6.2 Odometer


6.3 Data Fusion Based on Kalman Filter


First Task: SLAM Practice of Multi-sensor Fusion



Chapter 7: Robotic Arm Motion Control


7.1 Robotic Arm


7.2 Robotic Arm Control:MoveIt!


First Task: Move the Robotic Arm:MoveIt! and Gazebo Simulation



Chapter 8: Machine Vision


8.1 Understanding OpenCV


8.2 Use the Monocular Vision Sensor


First Task: Install Monocular Camera Driver


8.3 Camera Calibration


8.4 Image Processing Based on Vision Sensor


8.5 Target Recognition Based on OpenCV


Second Task: Identify Objects



Chapter 9: Object Grasping with Vision-based Robotic Arm

9.1 Use the Depth Camera


First Task: Install Depth Camera Driver


9.2 Perceive:Object Recognition Based on Depth Camera


Second Task: Object Recognition based on Convolutional Neural Network


9.3 Hand-eye Calibration


Third Task: Use the "easy_handeye" Function Package


9.4 Plan:Grasp gesture generation


Fourth Task: Robotic Arm Grasp Objects



Chapter 10:Vision-based Mobile Robot


10.1 Vision-based Object Recognition and Positioning


10.2 Visual Servoing of Mobile Robots


First Task: Move Robotic Arm to Grasp Objects



Chapter 11:Visual SLAM and 3D Reconstruction


11.1 Framework of Classic Visual SLAM


First Task: Use rtab_map for 3D Positioning and Mapping


11.2 ORB-SLAM2 Algorithm


11.3 VINS-Fusion Algorithm


11.4 3D Reconstruction Based On Dense SLAM


Second Task: Use Depth Camera for Navigation


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Product Details
EAN
9789819918133
ISBN
9819918138
Publisher
Other Information
Illustrated
Dimensions
23.4 x 15.6 x 3.2 centimeters (1.04 kg)

Table of Contents

Chapter 1:The Composition of Typical Robot System.- Chapter 2:Connect the Robot to ROS.- Chapter 3:Preliminary Construction of Robot System Model.- Chapter 4:Laser SLAM.- Chapter 5: Autonomous Navigation.- Chapter 6: SLAM Based on Multiple Sensors.- Chapter 7: Robotic Arm Motion Control.- Chapter 8: Machine Vision.- Chapter 9: Object Grasping with Vision-based Robotic Arm.- Chapter 10:Vision-based Mobile Robot.- Chapter 11:Visual SLAM and 3D Reconstruction.

About the Author

Gang Peng, PhD, has research interests in intelligent robotics and intelligent manufacturing systems, intelligent sensing and control based on sensor fusion, intelligent analysis of industrial big data, AI, and machine learning algorithms. He has long been engaged in teaching, research, and development of intelligent robot control, multi-sensor integration and information fusion, intelligent driving, and human-robot collaborative systems. He has edited and published three Chinese monographs and one Springer English monograph. He has co-edited two Chinese monographs and one English translation. Additionally, as the first author or corresponding author, he has published papers in IEEE Transactions and other international journals in the field of robotics and automation, and has been granted more than 30 patents. Furthermore, he has presided over and completed the product transfer of scientific and technological achievements. He has been awarded the Outstanding Instructor Award of Huazhong University of Science and Technology for national major competitions and science and technology innovation many times and has supervised graduate students who have won provincial and municipal innovation and entrepreneurial talent awards.

Tin Lun LAM, PhD, Senior member of IEEE, serves as an assistant professor at Chinese University of Hong Kong (Shenzhen), Executive Deputy Director of the National-local Joint Engineering Laboratory of Robotics and Intelligent Manufacturing, and Director of Research at the Center on Intelligent Robots of Shenzhen Institute of Artificial Intelligence and Robotics for Society. His research focus includes new mobile robots, multi-robot systems, field robotics, soft robotics, and human-robot interaction. He has published two monographs and over 50 papers in top international journals and conferences in the field of robotics and automation and has been granted more than 60 patents. He has received the IEEE/ASME T-MECH Best Paper Award andIROS Best Paper Award on Robot Mechanisms and Design.

Chunxu Hu, the founder of the robotics community “Guyuehome,” obtained his master’s degree from the School of Artificial Intelligence and Automation of Huazhong University of Science and Technology. He focuses on the promotion and application of robot operating system and is an evangelist of the China ROS Foundation. He has been awarded the honorary title of one of the 10 most influential people in ROS in 2019.

Yu Yao, PhD, has been teaching, researching, and developing computer operating systems, AI technologies, and machine learning algorithms for many years.

Jintao Liu, PhD, the founder of ExBot Robotics Lab, has translated and published more than ten ROS books and is dedicated to the promotion and application of robot operating system.

Fan Yang, extramural advisor of graduate student at Tsinghua University, has been dedicated to the research of intelligent robots and intelligent hardware innovation and entrepreneurship. He has completed the marketing of several products, achieving good economic and social benefits. He is one of the editors of China’s White Paper on Artificial Intelligence Education, an evangelist of the China ROS Foundation, and a co-founder of the “Spark Project” ROS public classes.

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