Machine Learning for Robotics Applications

✍ Scribed by Monica Bianchini (editor), Milan Simic (editor), Ankush Ghosh (editor), Rabindra Nath Shaw (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 175
• Series: Studies in Computational Intelligence 960
• Category: Library

✦ Synopsis

Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas of applications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.

✦ Table of Contents

Preface
Contents
Editors and Contributors
Manipulation of Standard Link Mechanism for Robotic Application Using Artificial Neural Network and PID
1 Introduction
2 Modelling the Robot
2.1 Properties of PUMA 560
2.2 Manipulator Dynamics
2.3 Input and Output Data
3 Simulation with Artificial Neural Network (ANN)
3.1 Influence of Learning Functions
3.2 Optimised Simulated Results (File:Set49)
3.3 Simulation for Inverse Kinematics (Large Data Sets)
3.4 Optimised Simulated Results: (File-Rev28)
4 Simulation Using PID Controller
4.1 General
4.2 Control Using Error from Joint Rotations (Qi)
5 Conclusions
References
Machine Learning-Enabled Human Activity Recognition System for Humanoid Robot
1 Introduction
2 Related Works
3 Motivation of the Work
4 Methodologies
4.1 Dataset
4.2 Data Preprocessing
4.3 Models
4.4 Evaluation Metrics Used
5 Simulation Results
6 Conclusions
References
Hospital Assistance Robots Control Strategy and Machine Learning Technology
1 Introduction
2 Literature Survey
3 Description
3.1 Sliding Mode Controller (SMC)
3.2 Back Stepping Controller
3.3 Machine Learning
4 Conclusion
5 Future Scope
References
Cyber Physical System Fraud Analysis by Mobile Robot
1 Introduction
1.1 Machine Learning Algorithms in CPS
2 Related Work
3 Proposed Work
4 Proposed Model
5 Conclusion and Future Work
References
Design and Development of an Intelligent Robot for Improving Crop Productivity Using Machine Learning
1 Introduction
1.1 A Subsection Sample
2 Literature Survey
3 System Architecture
4 Process Description
5 Convolutional Neural Network (CNN)
6 Conclusions and Further Development
References
Integration of Wireless Sensor Network in Robotics
1 Introduction
2 Wireless Sensor Network
2.1 Applications of WSNs
2.2 Design Issues in WSNs
3 Robot and Robotics
3.1 Main Components of a Robot
3.2 Applications of Robot
4 Collaboration Between WSNs and Robotics
4.1 Challenges in RWSN
5 Conclusion
References
Digital Transformation in Smart Manufacturing with Industrial Robot Through Predictive Data Analysis
1 Introduction
2 Digital Transformation in Smart Factory
2.1 Better Manufacturing Cycles
2.2 Growing Call for Customization
2.3 Strengthened Merchandise
3 Data Driven in Smart Manufacturing
4 Robotic Machine Management Index
5 Results and Discussion
6 Conclusions
References
Surveillance Robot in Cyber Intelligence for Vulnerability Detection
1 Introduction
2 Literature Review
3 Methodology to Analyze Cyber Threats in Robotic Application
4 Modeling Robot Cyber Security Threats
5 Cyber Security-Enabled Research Data for Robotic Applications
6 Cyber Security Attack Scenario
7 Robotics Application in Military Surveillance
8 Implementation of Advanced Technological Architecture for the Protection from Security Breach
9 Market Architecture for Cyber Security-Enabled Robotics
10 AI-Enabled Robots to Analyze Malicious Patterns
11 Cyber Terrorism Using Autobots
12 Future Trends in Robotics
13 Conclusion
References
Framework and Smart Contract for Blockchain Enabled Certificate Verification System Using Robotics
1 Introduction
2 Literature Survey
3 Methodology
3.1 Step 1. Designing a Smart Contract
3.2 Step2. Writing Smart Contract in Solidity Using Sublime Text3
3.3 Step 3. Importing, Compiling and Testing Smart Contract into Remix Ethereum Integrated Development Environment
4 Result
5 Conclusion
References
Design of a Machine Learning-Based Self-driving Car
1 Introduction
2 Basics of Machine Learning
2.1 Supervised Learning
2.2 Unsupervised Learning
3 Methodology
3.1 Behavior Cloning
3.2 Image Augmentation
3.3 Convolutional Neural Network Architecture
4 Training and Results
5 Conclusion
References
Prediction of Traffic Movement for Autonomous Vehicles
1 Introduction
2 Related Work
2.1 Perception Datasets
2.2 Prediction Datasets
3 Dataset
3.1 Rasterization
3.2 Visualization
4 Results and Discussions
5 Conclusions
References