1CHAPTER 1 Introduction to Robotics
395.2 Feature Extraction and Matching
21.1 Definition and Scope of Robotics
405.2.1 Feature Detection
31.2 History of Robotics
415.3.2 Feature Descriptors
41.3 Components of Robotic Systems
425.3.3 Feature Matching Algorithms
51.4 Applications of Robotics
435.3.4 Feature-Based Registration and Alignment
6CHAPTER 2 Kinematics of Robots
445.3.5 Deep Learning Approaches
72.1 Degrees of Freedom and Motion Types
455.5 Visual Servoing and Hand-Eye Calibration
82.2 Forward Kinematics
46CHAPTER 6 Robotic Manipulation
92.1.1 Denavit-Hartenberg Parameters
476.1 End-Effector Design and Grippers
102.1.2 Homogeneous Transformation Matrices
486.2 Forward and Inverse Kinematics for Manipulators
112.1.3 Forward Kinematics Solutions for Serial Manipulators
496.3 Path Planning and Collision Avoidance
122.1.4 Closed-form Solutions vs. Numerical Methods
506.4 Grasping and Manipulation Strategies
132.1.5 Forward Kinematics for Parallel Manipulators
516.5 Cooperative Manipulation and Multi-Robot Systems
142.3 Inverse Kinematics
52CHAPTER 7
152.4 Jacobian Matrix and Velocity Kinematics
53Mobile Robots and Navigation
162.5 Singularities and Workspace Analysis
547.1 Mobile Robot Architectures
17CHAPTER 3 Dynamics and Control of Robots
557.2 Localization and Mapping (SLAM)
183.1 Newton-Euler Formulation
567.3 Path Planning and Obstacle Avoidance
193.2 Lagrange-Euler Formulation
577.4 Simultaneous Localization and Mapping (SLAM)
203.3 Dynamic Equations of Motion
587.5 Multi-Robot Coordination and Swarm Intelligence
213.3.1 Euler-Lagrange Equations
59CHAPTER 8 Human-Robot Interaction
223.3.2 Newton-Euler Equations
608.1 Interface Design
233.3.3 Dynamic Modeling of Serial and Parallel Robots
618.2 Teleoperation and Shared Control
243.3.4 Dynamic Parameters Estimation
628.3 Collaborative Robotics in Industry
253.3.5 Dynamic Control Algorithms
638.4 Ethical Considerations
263.4 Feedback Control Techniques
64CHAPTER 9 Robot Learning and Adaptation
273.5 Trajectory Planning and Control Strategies
659.2 Imitation Learning and Apprenticeship
28CHAPTER 4 Sensors and Perception in Robotics
669.3 Transfer Learning in Robotics
294.2.1 Intrinsic and Extrinsic Calibration
679.4 Adaptive Control and Online Learning
304.2.2 Calibration Techniques
689.5 Cognitive Robotics and Developmental Robotics
314.2.3 Sensor Fusion Techniques
69CHAPTER 10 Robot Applications in Industry and Beyond
324.2.4 Calibration Tools and Software
7010.1 Industrial Robotics
334.2.5 Challenges in Sensor Fusion
7110.2 Service Robotics
344.3 Localization and Mapping (SLAM)
7210.3 Agricultural Robotics
354.4 Object Recognition and Tracking
7310.4 Space Robotics
364.5 Machine Learning in Perception
7410.5 Future Trends and Emerging Applications
37CHAPTER 5 Robot Vision Systems
75Glossary
385.1 Imaging Basics
76Index
