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Introduction to Intelligent Robot System Design Gang Peng

Introduction to Intelligent Robot System Design By Gang Peng

Introduction to Intelligent Robot System Design by Gang Peng

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Introduction to Intelligent Robot System Design Summary

Introduction to Intelligent Robot System Design: Application Development with ROS by Gang Peng

This book introduces readers to the principles and practical applications of intelligent robot system with robot operating system (ROS), pursuing a task-oriented and hands-on approach. Taking the conception, design, implementation, and operation of robot application systems as a typical project, and through learning-by-doing, practicing-while-learning approach, it familiarizes readers with ROS-based intelligent robot system design and development step by step.

The topics covered include ROS principles, mobile robot control, Lidar, simultaneous localization and mapping (SLAM), navigation, manipulator control, image recognition, vision calibration, object grasping, vision SALM, etc., with typical practical application tasks throughout the book, which are essential to mastering development methods for intelligent robot system.

Easy to follow and rich in content, the book can be used at colleges and universities as learning material and a teaching reference book for intelligent robot, autonomous intelligent system, robotics principles, and robot system application development with ROS in connection with automation, robotics engineering, artificial intelligence (AI), mechatronics, and other related majors. The book can assist in mastering the development and design of robot systems and provide the necessary theoretical and practical references to cultivate robot system development capabilities and can be used as teaching material for engineering training and competitions, or for reference, self-study, and training by engineering and technical personnel, teachers, and anyone who wants to engage in intelligent robot system development and design.


About Gang Peng

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 and IROS 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.


Table of Contents

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

Additional information

NPB9789819918133
9789819918133
9819918138
Introduction to Intelligent Robot System Design: Application Development with ROS by Gang Peng
Gang Peng
New
Hardback
Springer Verlag, Singapore
2023-09-05
569
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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