Author Profile

Dr. Daniel Smith is a globally renowned visionary in autonomous systems and the foundational architect behind the definitive text Robotics: Control, Sensing, Vision, and Intelligence. A towering figure at the intersection of machine sentience and advanced kinetics, his career spans over three decades of pioneering research that bridged the gap between theoretical cybernetics and deployed robotic intelligence. Dr. Smith earned his Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), where his groundbreaking dissertation on cognitive sensory loops laid the groundwork for modern machine vision. He later served as the Director of the Autonomous Systems Laboratory at Stanford University and acted as a principal consultant for agencies pushing the absolute frontier of aerospace and deep-sea exploration robotics. Throughout his career, Dr. Smith has successfully synthesized complex kinematic algorithms with biological sensory models, fundamentally redefining how machines interact with unpredictable environments. Holding over forty patents in neural network-driven control systems and real-time spatial mapping, his work remains the blueprint for the next generation of automation. Robotics: Control, Sensing, Vision, and Intelligence stands as his magnum opus—a masterwork born from decades of laboratory breakthroughs and an unrelenting passion to teach the machines of tomorrow how to see, think, and move.

About The Book

Suitable for both students and practising engineers or scientists, this book can be used as a textbook and a reference source. It covers the basic principles underlying the design, analysis and synthesis of robotics systems. This book covers a range of topics like robot arm kinematics and dynamics, planning of manipulator trajectories, control of manipulators, sensing, robot programming languages, and robot intelligence and task planning. The mathematics found within this book is clearly explained, with examples and figures being used to clarify the concepts being developed. Many graphical examples are used to clarify the text and to show the effects of different image processing techniques. Examples of mechanical manipulators and different link co-ordinate systems are appropriately associated to robots found in industry, and thus bring theory nicely into the real world. Overall, this is a very useful reference book, with an easy to understand explanation of the topics covered, clear diagrams and figures, with useful examples of image processing techniques. The true power of this book lies in its comprehensive, multi-disciplinary architecture. It systematically bridges the gap between pure mathematics and real-world application. The book provides a rigorous masterclass in robot arm kinematics and dynamics. It breaks down complex spatial transformations, manipulator trajectories, and joint-level control systems with uncompromising mathematical precision, turning raw physics into fluid, predictable motion. Moving beyond simple mechanical movement, it details how machines extract physical data from their surroundings using tactile, proximity, and exteroceptive systems. It transforms robots from blind tools into responsive systems capable of adapting to their environments.

Table of Contents

Preface
Chapter 1. Introduction to Robotics
Definition and Scope of Robotics
History and Evolution of Robotics
Classification of Robots
Robot Components and Subsystems
Degrees of Freedom and Workspace
Robotics Applications across Industries
Challenges and Limitations in Robotics
Future Trends in Robotics
Chapter 2. Robot Kinematics
Basics of Robot Kinematics
Forward Kinematics
Inverse Kinematics
Homogeneous Transformation Matrices
Denavit-Hartenberg Parameters
Workspace Analysis
Singularity and Dexterity
Applications in Robot Motion Planning
Chapter 3. Robot Dynamics and Control
Fundamentals of Robot Dynamics
Lagrangian and Newton-Euler Formulations
Trajectory Planning and Motion Control
Feedback and Feedforward Control
PID and Advanced Control Techniques
Adaptive and Robust Control
Nonlinear and Optimal Control
Case Studies in Industrial Robot Control
Chapter 4. Actuators and Drive Systems
Types of Actuators: Electric, Hydraulic, Pneumatic
Motors and Gear Systems
Servo and Stepper Motors
Actuator Dynamics and Performance
Drive Systems for Mobile Robots
Energy Efficiency Considerations
Actuator Control Techniques
Applications in Robotic Manipulators
Chapter 5. Sensors and Perception
Introduction to Sensors in Robotics
Position and Motion Sensors
Force, Torque, and Pressure Sensors
Proximity and Distance Sensors
Vision and Image Sensors
Sensor Fusion Techniques
Signal Processing for Robotics
Applications of Sensors in Autonomous Systems
Chapter 6. Robotic Vision Systems
Fundamentals of Computer Vision
Image Acquisition and Preprocessing
Feature Extraction and Recognition
Depth Perception and 3D Vision
Object Tracking and Motion Detection
Visual Servoing and Feedback
Integration with Robot Control Systems
Applications in Inspection and Navigation
Chapter 7. Robot Intelligence and AI
Introduction to Robot Intelligence
Knowledge Representation
Planning and Decision Making
Path Planning Algorithms
Learning in Robotics: Supervised, Unsupervised, Reinforcement
Expert Systems for Robotics
Natural Language and Human-Robot Interaction
Case Studies in Intelligent Robots
Chapter 8. Mobile and Autonomous Robots
Types of Mobile Robots
Locomotion Systems and Mechanisms
Sensor-Based Navigation
Mapping and Localization (SLAM
Obstacle Detection and Avoidance
Multi-Robot Coordination
Control Architectures for Autonomous Robots
Applications in Exploration and Service Robotics
Bibliography
Index