This book describes visual perception and control methods for robotic systems that need to interact with the environment. Multiple view geometry is utilized to extract low-dimensional geometric information from abundant and high-dimensional image information, making it convenient to develop general solutions for robot perception and control tasks. In this book, multiple view geometry is used for geometric modeling and scaled pose estimation. Then Lyapunov methods are applied to design stabilizing control laws in the presence of model uncertainties and multiple constraints.
1. Foundations: Robotics. 2. Multiple View Geometry. 3. Visual Perception of Robotics: Introduction to Visual Perception. 4. Two-view Geometry-based Road Scene Reconstruction. 5. Recursive Road Detection with Shadows. 6. Range Identification of Moving Objects Using a Single Camera. 7. Velocity and Range Identification of Moving Objects Using a Static-moving Camera System. 8. Visual Control of Robotics: Introduction to Visual Control. 9. Homography-based Visual Servo Tracking for a Fixed Camera Configuration with a Camera-in-hand Extension. 10. Navigation Function-based Visual Control with Field-of-view Constraints. 11. Robust Control for Moving Object Tracking with Trajectory Tracking Extension. 12. Trifocal Tensor-based Unified Tracking and Regulation of Wheeled Mobile Robots. 13. Homography-based Unified Tracking and Regulation of Wheeled Mobile Robots with Euclidean Reconstruction. 14. Conclusion and Future Research Directions.