Robot Manipulators Robot Manipu lato rs Edited by Marco Ceccarelli I-Tech Published by In-Teh In-Teh is Croatian branch of I-Tech Education and Publishing KG, Vienna, Austria. 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. © 2008 In-teh www.in-teh.org Additional copies can be obtained from: publication@ars-journal.com First published September 2008 Printed in Croatia A catalogue record for this book is available from the University Library Rijeka under no. 111222001 Robot Manipulators, Edited by Marco Ceccarelli p. cm. ISBN 978-953-7619-06-0 1. Robot Manipulators. I. Marco Ceccarelli V Preface Robots can be considered as the most advanced automatic systems and robotics, as a technique and scientific discipline, can be considered as the evolution of automation with in- terdisciplinary integration with other technological fields. A robot can be defined as a system which is able to perform several manipulative tasks with objects, tools, and even its extremity (end-effector) with the capability of being re- programmed for several types of operations. There is an integration of mechanical and con- trol counterparts, but it even includes additional equipment and components, concerned with sensorial capabilities and artificial intelligence. Therefore, the simultaneous operation and design integration of all the above-mentioned systems will provide a robotic system The State-of-Art of Robotics already refers to solutions of early 70s as very obsolete de- signs, although they are not yet worthy to be considered as pertaining to History. The fact that the progress in the field of Robotics has grown very quickly has given a shorten of the time period for the events being historical, although in many cases they cannot be yet ac- cepted as pertaining to the History of Science and Technology. It is well known that the word “robot” was coined by Karel Capek in 1921 for a theatre play dealing with cybernetic workers, who/which replace humans in heavy work. Indeed, even in today life-time robots are intended with a wide meaning that includes any system that can operate autonomously for given class of tasks. Sometimes intelligent capability is included as a fundamental property of a robot, as shown in many fiction works and movies, although many current robots, mostly in industrial applications, have only flexible pro- gramming and are very far to be intelligent machines. From technical viewpoint a unique definition of robot has taken time for being univer- sally accepted. In 1988 the International Standard Organization gives: “An industrial robot is an auto- matic, servo-controlled, freely programmable, multipurpose manipulator, with several axes, for the handling of work pieces, tools or special devices. Variably programmed operations make possible the execution of a multiplicity of tasks”. However, still in 1991 for example, the IFToMM International Federation for the Promo- tion and Mechanism and Machine Science (formerly International Federation for the Theory of Machines and Mechanisms) gives its own definitions: Robot as “Mechanical system under automatic control that performs operations such as handling and locomotion”; and Manipu- lator as ”Device for gripping and controlled movements of objects”. Even roboticists use their own definition for robots to emphasize some peculiarities, as for example from IEEE Community: “a robot is a machine constructed as an assemblage of joined links so that they can be articulated into desired positions by a programmable con- troller and precision actuators to perform a variety of tasks”. However, different meanings for robots are still persistent from nation to nation, from technical field to technical field, from application to application. Nevertheless, a robot or robotic system can be recognized when it has the three main characteristics: mechanical versatility, reprogramming capacity, and intelligent capability. Summarizing briefly the concepts, one can understand the above-mentioned terms as fol- lows; mechanical versatility refers to the ability of the mechanical design to perform several different manipulative tasks; reprogramming capacity concerns with the possibility to up- VI date the operation timing and sequence, even for different tasks, by means of software pro- gramming; intelligent capability refers to the skill of a robot to recognize its owns state and neighbour environment by using sensors and human-like reasoning, even to update auto- matically the operation. Therefore, a robot can be considered as a complex system that is composed of several sys- tems and devices to give: - mechanical capabilities (motion and force); - sensorial capabilities (similar to human beings and/or specific others); - intellectual capabilities (for control, decision, and memory). In this book we have grouped contributions in 28 chapters from several authors all around the world on the several aspects and challenges of research and applications of ro- bots with the aim to show the recent advances and problems that still need to be considered for future improvements of robot success in worldwide frames. Each chapter addresses a specific area of modeling, design, and application of robots but with an eye to give an inte- grated view of what make a robot a unique modern system for many different uses and fu- ture potential applications. Main attention has been focused on design issues as thought challenging for improving capabilities and further possibilities of robots for new and old applications, as seen from to- day technologies and research programs. Thus, great attention has been addressed to con- trol aspects that are strongly evolving also as function of the improvements in robot model- ing, sensors, servo-power systems, and informatics. But even other aspects are considered as of fundamental challenge both in design and use of robots with improved performance and capabilities, like for example kinematic design, dynamics, vision integration. Maybe some aspects have received not a proper attention or discussion as an indication of the fecundity that Robotics can still express for a future benefit of Society improvement both in term of labor environment and productivity, but also for a better quality of life even in other fields than working places. Thus, I believe that a reader will take advantage of the chapters in this edited book with further satisfaction and motivation for her or his work in professional applications as well as in research activity. I thank the authors who have contributed with very interesting chapters in several sub- jects, covering the many fields of Robotics. I thank the editor I-Tech Education and Publish- ing KG in Wien and its Scientific Manager prof Aleksandar Lazinica for having supported this editorial initiative and having offered a very kind editorial support to all the authors in elaborating and delivering the chapters in proper format in time. Editor Marco Ceccarelli LARM: Laboratory of Robotics and Mechatronics, DiMSAT - University of Cassino Via Di Biasio 43, 03043 Cassino (Fr), Italy VII Contents Preface V 1. Experimental Results on Variable Structure Control for an Uncertain Robot Model 001 K. Bouyoucef, K. Khorasani and M. Hamerlain 2. Unit Quaternions: A Mathematical Tool for Modeling, Path Planning and Control of Robot Manipulators 021 Ricardo Campa and Karla Camarillo 3. Kinematic Design of Manipulators 049 Marco Ceccarelli and Erika Ottaviano 4. Gentle Robotic Handling Using Acceleration Compensation 073 Suei Jen Chen 5. Calibration of Robot Reference Frames for Enhanced Robot Positioning Accuracy 095 Frank Shaopeng Cheng 6. Control of Robotic Systems Undergoing a Non-Contact to Contact Transition 113 S. Bhasin, K. Dupree and W. E. Dixon 7. Motion Control of a Robot Manipulator in Free Space Based on Model Predictive Control 137 Vincent Duchaine, Samuel Bouchard and Clément Gosselin 8. Experimental Control of Flexible Robot Manipulators 155 A. Sanz and V. Etxebarria 9. Improvement of Force Control in Robotic Manipulators Using Sensor Fusion Techniques 181 J. Gamez, A. Robertsson, J. Gomez Ortega and R. Johansson 10. Adaptive Neural Network Based Fuzzy Sliding Mode Control of Robot Manipulator 201 Ayca Gokhan AK and Galip Cansever VIII 11. Impedance Control of Flexible Robot Manipulators 211 Zhao-Hui Jiang 12. Simple Effective Control for Robot Manipulators with Friction 225 Maolin Jin, Sang Hoon Kang and Pyung Hun Chang 13. On transpose Jacobian control for monocular fixed-camera 3D Direct Visual Servoing 243 Rafael Kelly, Ilse Cervantes, Jose Alvarez-Ramirez, Eusebio Bugarin and Carmen Monroy 14. Novel Framework of Robot Force Control Using Reinforcement Learning 259 Byungchan Kim and Shinsuk Park 15. Link Mass Optimization Using Genetic Algorithms for Industrial Robot Manipulators 275 Serdar Kucuk and Zafer Bingul 16. FPGA-Realization of a Motion Control IC for Robot Manipulator 291 Ying-Shieh Kung and Chia-Sheng Chen 17. Experimental Identification of the Inverse Dynamic Model: Minimal Encoder Resolution Needed Application to an Industrial Robot Arm and a Haptic Interface 313 Marcassus Nicolas, Alexandre Janot, Pierre-Olivier Vandanjon and Maxime Gautier 18. Towards Simulation of Custom Industrial Robots 331 Cosmin Marcu and Radu Robotin 19. Design and Simulation of Robot Manipulators using a Modular Hardware-in-the-loop Platform 347 Adrian Martin and M. Reza Emami 20. Soft-computing Techniques for the Trajectory Planning of Multi-robot Manipulator Systems 373 Emmanuel A. Merchán-Cruz, Alan S. Morris and Javier Ramírez-Gordillo 21. Robot Control Using On-Line Modification of Reference Trajectories 399 Javier Moreno-Valenzuela 22. Motion Behavior of Null Space in Redundant Robotic Manipulators 413 Tsuyoshi Shibata and Toshiyuki Murakami 23. Paddle Juggling by Robot Manipulator with Visual Servo 425 Akira Nakashima, Yoshiyasu Sugiyama and Yoshikazu Hayakawa 24. An Industrial Robot as Part of an Automatic System for Geometric Reverse Engineering 441 Mohamed Rahayem IX 25. Sensing Planning of Calibration Measurements for Intelligent Robots 459 Mikko Sallinen and Tapio Heikkilä 26. Robot Programming in Machining Operations 479 Bjørn Solvang, Gabor Sziebig and Peter Korondi 27. Dynamic Visual Servoing with an Uncalibrated Eye-in-hand Camera 497 Hesheng Wang and Yun-Hui Liu 28. Vision-Guided Robot Control for 3D Object Recognition and Manipulation 521 S. Xie, E Haemmerle, Y. Cheng and P. Gamage [...]... Experimental Results on Variable Structure Control for an Uncertain Robot Model 3 (a) The SCARA Robot RP41 (b) Schematic of the SCARA RP41 mechanism Figure 1 The SCARA Robot Manipulator (RP 41), (Centre de Développement des Technologies Avancées, Algiers) Digital controller output 0 2048 4096 D/A Converter output [volts] +5 0 -5 Robot DC motors input [volts] +24 0 -24 Table 1 Digital and analog control... 5 Volts In order to activate the DC drive of each robot joint, these low voltages are amplified by a power board to the range of -24 to +24 Volts In virtue of the robustness properties, uncertain linear models of the robot are obtained for the design of the SM-VS controllers This section briefly presents the experimental identification of the three robot axes resulting in a suitable second order linear... Variable Structure (GVSC) control techniques are implemented on the Robot Manipulator (RP41) as illustrated in Fig 1-a From the schematic that is depicted in Fig 1-b, one can observe that the RP41 is a SCARA robot with four degrees of freedom The three first joints (J1, J2, and J3) are rotoide while the fourth one (T) is prismatic To each robot axis, one assigns a controller that uses only a measured angular... the off-line identification generated the robot parameters according to model (2), which are illustrated in Table 1 A0 = diag [- 5.4 - 2.41 - 117] A1 = diag [560.7 200 413.5] B = diag [0.5 0.65 7.5] Table 1 The identification of the robot parameters corresponding to model (2) Note that in compliance with model (2), the obtained parameters correspond to the robot model that is used in the CVS control... Hamerlain, M & Bouyoucef, K (1998) Tracking trajectory for robot using Variable Structure Control, Proceeding of the 4th ECPD, International Conference on Advanced Robotics, Intelligent Automation and Active Systems, pp 207-212, 24-26 August 1998, Moscow Bouyoucef, K.; Kadri, M & Bouzouia, B (1998) Identification expérimentale de la dynamique du robot manipulateur RP41, 1er Colloque National sur la Productique,... Hamerlain M.; Belhocine, M & Bouyoucef, K (1997) Sliding Mode Control for a Robot SCARA, Proceeding of IFAC/ACE’97, pp153-157, 14-16 July 1997, Istambul, Turkey Harashima, E, Hashimoto H & Maruyama K (1986) Practical robust control of robot arm using variable structure systems, Proceeding of IEEE, International Conference on Robotics and automation, pp 532-538, 1986, San Francisco, USA Levant, A & Alelishvili... space employed, the following three aspects are of interest when designing and working with robot manipulators: • Modeling: The knowledge of all the physical parameters of the robot, and the relations among them Mathematical (kinematic and dynamic) models should be extracted from the physical laws ruling the robot s motion Kinematics is important, since it relates joint and pose coordinates, or their... joint space controllers or pose space controllers Robot control systems can be implemented either at a low level (e.g electronic controllers in the servo–motor drives) or via sophisticated high–level programs in a computer Fig 1 shows how these aspects are related to conform a robot motion control system By motion control we refer to the control of a robotic mechanism which is intended to track a desired... generated by a trajectory planner, either in joint or pose variables The motion controller can thus be designed either in joint or pose space, respectively 22 Robot Manipulators Figure 1 General scheme of a robot motion control system Most of industrial robot manipulators are driven by brushless DC (BLDC) servoactuators A BLDC servo system is composed by a permanent–magnet synchronous motor, and an electronic... numbers (Hamilton, 1844) Unit Quaternions: A Mathematical Tool for Modeling, Path Planning and Control of Robot Manipulators 23 The use of Euler parameters in robotics has increased in the latter years They are an alternative to rotation matrices for defining the kinematic relations among the robot s joint variables and the end–effector’s pose The advantage of using unit quaternions over rotation matrices, . Rijeka under no. 11 12220 01 Robot Manipulators, Edited by Marco Ceccarelli p. cm. ISBN 978-953-7 619 -06-0 1. Robot Manipulators. I. Marco Ceccarelli V Preface Robots can be. condition (11 ) should be satisfied Robot Manipulators 8 x hhhh rank x hhh rank ddd δ δ δ δ ),,,,(),,,( )( )1( )1( −− = "" (11 ) Defining a new variable 1 = i i y η where di , ,1 "=. generated the robot parameters according to model (2), which are illustrated in Table 1. [] 11 7- 41. 2-4.5- 0 diagA = [] 5. 413 2007.560 1 diagA = [ ] 5.765.05.0= diagB Table 1. The identification