edited by Koichi Hashimoto (Osaka University)

This book treats visual feedback control of mechanical systems, mostly robot manipulators. It not only deals with image processing techniques and robot control schemes but also covers the latest investigation of the design of the visual servo mechanism based on modern linear and nonlinear control theory, the adaptive control scheme, fuzzy logic, and neural networks. New concepts for utilizing visual sensory information for real-time manipulator control are derived and the performances are evaluated through simulations and/or experiments.

The contributors to this book are robotics specialists from all over the world. The book gives a practical perspective on visual servoing to researchers, engineers, and students working in this area.

• Visual Control of Robot Manipulators — A Review (P I Corke)
• Hand-Eye Coordination for Robotic Tracking and Grasping (P K Allen et al.)
• Visual Servo Control of Robots Using Kalman Filter Estimates of Robot Pose Relative to Work-Pieces (W J Wilson)
• Feature-Based Visual Servoing of Robotic Systems (J T Feddema et al.)
• Visual Servoing for Robotic Assembly (B Nelson et al.)
• LQ Optimal and Nonlinear Approaches to Visual Servoing (K Hashimoto & H Kimura)
• Classification and Realization of the Different Vision-Based Tasks (F Chaumette et al.)
• A Dynamic Sensor for Robot Juggling (A A Rizzi & D E Koditschek)
• Video-Rate Robot Visual Servoing (P I Corke)
• Visual Servoing of Robot Manipulators by Fuzzy Membership Function Based Neural Networks (I H Suh & T W Kim)
• Characterization and Use of Feature-Jacobian Matrix for Visual Servoing (Z Bien et al.)