Robotics: Control, Sensing, Vision, and Intelligence

By Daniel Smith
327
2026

Description

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.

About Author

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.

Table of Content

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