Applied Linear Algebra for Robot Systems Volume 3: Mathematics for Robotics, Automation and Intelligent Machines (Foundation on Robotics : Mathematics, Physics & Programming for Robotics)

This book guide readers through the planning, construction, testing, and future development of a linear-algebra-driven autonomous mobile inspection robot. Students learn how to transform an engineering idea into requirements, calculations, mechanical layout, sensor placement, power planning, firmware structure, and safety procedures. The capstone project then moves into real prototype construction, where wheel alignment, motor mounting, encoder direction, IMU orientation, sensor calibration, grounding, and power integrity are treated as essential parts of the mathematical model.

The final capstone testing chapter teaches students how to validate a robot systematically through encoder calibration, wheel-distance correction, IMU bias removal, motor response testing, path-following validation, obstacle detection, repeatability measurement, battery endurance testing, data logging, debugging, and final deployment. The closing chapter expands the reader’s view toward advanced robotics, showing how the same linear algebra foundations appear in SLAM, machine vision, collaborative robots and future research. Together, these chapters complete the learning journey by showing that applied linear algebra is not only a mathematical subject, but a practical engineering tool for designing, building, testing, troubleshooting and advancing real robotic systems.

If you're ready to strengthen your mathematical thinking and connect it directly to robotics and intelligent systems, this is where your journey gains precision and clarity.