Mechatronics Experiments with Machine Vision
Description
This book is an interactive guide that blends hands-on experimentation with modern learning approaches. Instead of traditional instruction, the book presents a series of quests-practical challenges that encourage readers to explore, simulate, and build real-world mechatronic systems. From JavaScript-based simulations to sensor integration and video feedback control, each chapter builds technical skills through discovery and problem-solving. Alongside the technical content, the book reflects on how learning itself is evolving in the age of AI, emphasizing creativity, adaptability, and achievement over rote memorization. Supported by a companion website full of code and examples, this book is ideal for students, educators, and enthusiasts eager to learn by doing.
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Person
Emeritus Professor John Billingsley has recently retired from Chair of mechatronic engineering at the University of Southern Queensland in Toowoomba, where he also supervised Technology Research in a Centre for Engineering in Agriculture. Throughout his career, he has made significant contributions to the development of mechatronic systems, starting long ago with the control design of a commercial autopilot. Industrial consultancies include pioneering work in laser phototypesetting, acoustic telescopes, and wall-climbing robots. He is the originator and for some thirty years has been International Chairman of the annual "Mechatronics and Machine Vision in Practice" conference series and has been recognized for his achievements with an achievement medal from the Institution of Engineering and Technology, London, and Erskine Fellowship from the University of Canterbury, NZ. His innovative machines have been exhibited in notable institutions such as the Palais de la Découverte in Paris, the Exploratorium in San Francisco, and the Powerhouse Museum in Sydney.
Content
Simulating a Dynamic System.- A balancing problem.- Design and build.- Sensors for consumer devices.- Detection of Errors and Faults in Data.- Basics of Machine Vision.- Precision motor control.- A video control loop.- 2D Control with Vision.- Turning Heads.- Exploring Bluetooth.- Using s-psi for recognition.- AI, Love and Hate.
