Table Of Content

I Robot Vision Robot Vision Edited by Aleš Ude In-Tech intechweb.org Published by In-Teh In-Teh Olajnica 19/2, 32000 Vukovar, Croatia Abstracting and non-profit use of the material is permitted with credit to the source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. Publisher assumes no responsibility liability for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained inside. After this work has been published by the In-Teh, authors have the right to republish it, in whole or part, in any publication of which they are an author or editor, and the make other personal use of the work. © 2010 In-teh www.intechweb.org Additional copies can be obtained from: [email protected] First published March 2010 Printed in India Technical Editor: Martina Peric Cover designed by Dino Smrekar Robot Vision, Edited by Aleš Ude p. cm. ISBN 978-953-307-077-3 V Preface The purpose of robot vision is to enable robots to perceive the external world in order to perform a large range of tasks such as navigation, visual servoing for object tracking and manipulation, object recognition and categorization, surveillance, and higher-level decision- making. Among different perceptual modalities, vision is arguably the most important one. It is therefore an essential building block of a cognitive robot. Most of the initial research in robot vision has been industrially oriented and while this research is still ongoing, current works are more focused on enabling the robots to autonomously operate in natural environments that cannot be fully modeled and controlled. A long-term goal is to open new applications to robotics such as robotic home assistants, which can only come into existence if the robots are equipped with significant cognitive capabilities. In pursuit of this goal, current research in robot vision benefits from studies in human vision, which is still by far the most powerful existing vision system. It also emphasizes the role of active vision, which in case of humanoid robots does not limit itself to active eyes only any more, but rather employs the whole body of the humanoid robot to support visual perception. By combining these paradigms with modern advances in computer vision, especially with many of the recently developed statistical approaches, powerful new robot vision systems can be built. This book presents a snapshot of the wide variety of work in robot vision that is currently going on in different parts of the world. March 2010 Aleš Ude VII Contents Preface V 1. Design and fabrication of soft zoom lens applied in robot vision 001 Wei-Cheng Lin, Chao-Chang A. Chen, Kuo-Cheng Huang and Yi-Shin Wang 2. Methods for Reliable Robot Vision with a Dioptric System 013 E. Martínez and A.P. del Pobil 3. An Approach for Optimal Design of Robot Vision Systems 021 Kanglin Xu 4. Visual Motion Analysis for 3D Robot Navigation in Dynamic Environments 037 Chunrong Yuan and Hanspeter A. Mallot 5. A Visual Navigation Strategy Based on Inverse Perspective Transformation 061 Francisco Bonin-Font, Alberto Ortiz and Gabriel Oliver 6. Vision-based Navigation Using an Associative Memory 085 Mateus Mendes 7. Vision Based Robotic Navigation: Application to Orthopedic Surgery 111 P. Gamage, S. Q. Xie, P. Delmas and W. L. Xu 8. Navigation and Control of Mobile Robot Using Sensor Fusion 129 Yong Liu 9. Visual Navigation for Mobile Robots 143 Nils Axel Andersen, Jens Christian Andersen, Enis Bayramoğlu and Ole Ravn 10. Interactive object learning and recognition with multiclass support vector machines 169 Aleš Ude 11. Recognizing Human Gait Types 183 Preben Fihl and Thomas B. Moeslund 12. Environment Recognition System for Biped Robot Walking Using Vision Based Sensor Fusion 209 Tae-Koo Kang, Hee-Jun Song and Gwi-Tae Park VIII 13. Non Contact 2D and 3D Shape Recognition by Vision System for Robotic Prehension 231 Bikash Bepari, Ranjit Ray and Subhasis Bhaumik 14. Image Stabilization in Active Robot Vision 261 Angelos Amanatiadis, Antonios Gasteratos, Stelios Papadakis and Vassilis Kaburlasos 15. Real-time Stereo Vision Applications 275 Christos Georgoulas, Georgios Ch. Sirakoulis and Ioannis Andreadis 16. Robot vision using 3D TOF systems 293 Stephan Hussmann and Torsten Edeler 17. Calibration of Non-SVP Hyperbolic Catadioptric Robotic Vision Systems 307 Bernardo Cunha, José Azevedo and Nuno Lau 18. Computational Modeling, Visualization, and Control of 2-D and 3-D Grasping under Rolling Contacts 325 Suguru Arimoto, Morio Yoshida and Masahiro Sekimoto1 19. Towards Real Time Data Reduction and Feature Abstraction for Robotics Vision 345 Rafael B. Gomes, Renato Q. Gardiman, Luiz E. C. Leite, Bruno M. Carvalho and Luiz M. G. Gonçalves 20. LSCIC Pre coder for Image and Video Compression 363 Muhammad Kamran, Shi Feng and Wang YiZhuo 21. The robotic visual information processing system based on wavelet transformation and photoelectric hybrid 373 DAI Shi-jie and HUANG-He 22. Direct visual servoing of planar manipulators using moments of planar targets 403 Eusebio Bugarin and Rafael Kelly 23. Industrial robot manipulator guarding using artificial vision 429 Fevery Brecht, Wyns Bart, Boullart Luc Llata García José Ramón and Torre Ferrero Carlos 24. Remote Robot Vision Control of a Flexible Manufacturing Cell 455 Silvia Anton, Florin Daniel Anton and Theodor Borangiu 25. Network-based Vision Guidance of Robot for Remote Quality Control 479 Yongjin (James) Kwon, Richard Chiou, Bill Tseng and Teresa Wu 26. Robot Vision in Industrial Assembly and Quality Control Processes 501 Niko Herakovic 27. Testing Stereoscopic Vision in Robot Teleguide 535 Salvatore Livatino, Giovanni Muscato and Christina Koeffel 28. Embedded System for Biometric Identification 557 Ahmad Nasir Che Rosli IX 29. Multi-Task Active-Vision in Robotics 583 J. Cabrera, D. Hernandez, A. Dominguez and E. Fernandez 30. An Approach to Perception Enhancement in Robotized Surgery using Computer Vision 597 Agustín A. Navarro, Albert Hernansanz, Joan Aranda and Alícia Casals