Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms

Haptics applying manipulation of touch sensation with the interaction of computer applications, machines or human touch. However, robots that used haptics’ movement control are set up in lab-range and undevoted to works in substantial way particularly because of size factor and limited workspace. Ma...

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Main Author: Mansor, Nuratiqa Natrah
Format: Thesis
Language:English
English
Published: 2019
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Online Access:http://eprints.utem.edu.my/id/eprint/24687/1/Force%20And%20Position%20Based%20Haptic%20Bilateral%20Control%20System%20For%20Single%20Joint%20Robotic%20Arms.pdf
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institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Jamaluddin, Muhammad Herman

topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Mansor, Nuratiqa Natrah
Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms
description Haptics applying manipulation of touch sensation with the interaction of computer applications, machines or human touch. However, robots that used haptics’ movement control are set up in lab-range and undevoted to works in substantial way particularly because of size factor and limited workspace. Majority of invented robot cannot recognize the surfaces textures on the object that they are handling. Application of the common force sensors have a lot of limitations and handicap to the system. There are some uncertainties, instability and delay occurred in the system. This research embarks to design a model of bilateral master-slave haptic system and simulate with controllers of Proportional (P), Proportional-Derivative (PD) and Proportional-Integral-Derivative (PID) also implementation of Disturbance Observer (DOB) and Reaction Force Observer (RFOB). Next, analyze the ability and performance of the proposed controller in terms of position and force reading on single joint. To cut cost and duration, a small, commercial industrial robot is used as mechanism to work with haptic bilateral control system. Additionally, DOB and RFOB managed to transmit vivid force sensation by rejecting disturbance force and attain a robust motion control. Literally, the system is required to adjust according to the target position and compensate the forces earn from surrounding. Observation and study on the feedback of new adaptive design method DOB and RFOB is presented to compare with the conventional controller P, PD, and PID inside a bilateral control system. The performances of the proposed design are measured inside a simulation platform. From experiments, results signified that Kp=5, Kd=0.1 is the best value for PD and Kp=5, Ki=0.001, Kd=0.1 for PID. System employed with observers are more accurate and faster when ωn=50 for Differential Mode and ωn=500 for Common Mode. Apart from that, this research is potential to be apply on surgical robots or manufacturing for industry.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Mansor, Nuratiqa Natrah
author_facet Mansor, Nuratiqa Natrah
author_sort Mansor, Nuratiqa Natrah
title Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms
title_short Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms
title_full Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms
title_fullStr Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms
title_full_unstemmed Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms
title_sort force and position based haptic bilateral control system for single joint robotic arms
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Electrical Engineering
publishDate 2019
url http://eprints.utem.edu.my/id/eprint/24687/1/Force%20And%20Position%20Based%20Haptic%20Bilateral%20Control%20System%20For%20Single%20Joint%20Robotic%20Arms.pdf
http://eprints.utem.edu.my/id/eprint/24687/2/Force%20And%20Position%20Based%20Haptic%20Bilateral%20Control%20System%20For%20Single%20Joint%20Robotic%20Arms.pdf
_version_ 1747834088712044544
spelling my-utem-ep.246872021-10-05T09:45:02Z Force And Position Based Haptic Bilateral Control System For Single Joint Robotic Arms 2019 Mansor, Nuratiqa Natrah TJ Mechanical engineering and machinery Haptics applying manipulation of touch sensation with the interaction of computer applications, machines or human touch. However, robots that used haptics’ movement control are set up in lab-range and undevoted to works in substantial way particularly because of size factor and limited workspace. Majority of invented robot cannot recognize the surfaces textures on the object that they are handling. Application of the common force sensors have a lot of limitations and handicap to the system. There are some uncertainties, instability and delay occurred in the system. This research embarks to design a model of bilateral master-slave haptic system and simulate with controllers of Proportional (P), Proportional-Derivative (PD) and Proportional-Integral-Derivative (PID) also implementation of Disturbance Observer (DOB) and Reaction Force Observer (RFOB). Next, analyze the ability and performance of the proposed controller in terms of position and force reading on single joint. To cut cost and duration, a small, commercial industrial robot is used as mechanism to work with haptic bilateral control system. Additionally, DOB and RFOB managed to transmit vivid force sensation by rejecting disturbance force and attain a robust motion control. Literally, the system is required to adjust according to the target position and compensate the forces earn from surrounding. Observation and study on the feedback of new adaptive design method DOB and RFOB is presented to compare with the conventional controller P, PD, and PID inside a bilateral control system. The performances of the proposed design are measured inside a simulation platform. From experiments, results signified that Kp=5, Kd=0.1 is the best value for PD and Kp=5, Ki=0.001, Kd=0.1 for PID. System employed with observers are more accurate and faster when ωn=50 for Differential Mode and ωn=500 for Common Mode. Apart from that, this research is potential to be apply on surgical robots or manufacturing for industry. 2019 Thesis http://eprints.utem.edu.my/id/eprint/24687/ http://eprints.utem.edu.my/id/eprint/24687/1/Force%20And%20Position%20Based%20Haptic%20Bilateral%20Control%20System%20For%20Single%20Joint%20Robotic%20Arms.pdf text en public http://eprints.utem.edu.my/id/eprint/24687/2/Force%20And%20Position%20Based%20Haptic%20Bilateral%20Control%20System%20For%20Single%20Joint%20Robotic%20Arms.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=116940 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Electrical Engineering Jamaluddin, Muhammad Herman 1. Abut, T. and Soygüder, S., 2018. Haptic Industrial Robot Control and Bilateral Teleoperation by Using a Virtual Visual Interface. In: 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey, pp. 1-4. 2. Agboh, W. C., Yalcin, M. and Patoglu, V., 2016. A Six Degrees of Freedom Haptic Interface for Laparoscopic Training. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, pp. 1107-1112. 3. Arafsha, F., Zhang, L., Dong, H. and Saddik, A. E., 2015. Contactless Haptic Feedback: State of The Art. In: 2015 IEEE International Symposium on Haptic, Audio and Visual Environments and Games (HAVE), Ottawa, pp. 1-6. 4. Attaran, M., 1990. Robotics Applications in Manufacturing, Journal of Information Systems Management, 7(1), pp. 14-21. 5. Baran, E. A., Uzunovic, T. and Sabanovic, A., 2018. Performance Improvement of Bilateral Control Systems Using Derivative of Force. In: Robotica, 36(11), pp. 1-14. 6. Benali, A., Richard, P. and Bidaud, P., 2000. A Six DoF Haptic Interface for Medical Virtual Reality Applications: Design, Control and Human Factors. In: Proceedings IEEE Virtual Reality 2000, New Brunswick, New Jersey, pp. 284. 7. Bin, Q., Suihuai, Y., Xiaoming, S., Wen, F. and Yanpu, Y., 2015. A Comparative Study of The Physical Model and Virtual Model in Industrial Design. Journal of Theoretical and Applied Information Technology (JATIT), 48(2), pp. 1153-1159. 8. Bogoni, T., Scarparo, R. and Pinho, M., 2015. A Virtual Reality Simulator for Training Endodontics Procedures Using Manual Files. In: 2015 IEEE Symposium on 3D User Interfaces (3DUI), Arles, pp. 39-42. 9. Boian, R. F., Deutsch, J. E., Lee, C. S., Burdea, G. C. and Lewis, J., 2003. Haptic Effects for Virtual Reality-Based Post-Stroke Rehabilitation. In: 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003 Proceedings, pp. 247-253. 10. Chen, H., Zhang, B. and Zhang, G., 2015. Robotic Assembly, Handbook of Manufacturing Engineering and Technology, Springer, pp. 2347-2401. 11. Choi, C., Han, H., An, B. and Kim, J., 2006. Development of a Surgical Simulator for Laparoscopic Oesophageal Procedures. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, New York, pp. 819-822. 12. Cui, F., Zhang, M. and Mi, X., 2006. A Semi-Autonomous Teleoperation Method for Mending Robots Based on Virtual Reality and WLAN. In: 2006 International Conference on Mechatronics and Automation, Luoyang, Henan, pp. 1430-1435. 13. Darmoul, S., Abidi, M. H., Ahmad, A., Al-Ahmari, A. M., Darwish, S. M. and Hussein, H. M. A., 2015. Virtual Reality for Manufacturing: A Robotic Cell Case Study. In: 2015 International Conference on Industrial Engineering and Operations Management (IEOM), Dubai, pp. 1-7. 14. D'Auria, D., Persia, F. and Siciliano, B., 2015. A Low-Cost Haptic System for Wrist Rehabilitation. In: 2015 IEEE International Conference on Information Reuse and Integration, San Francisco, pp. 491-495. 15. Diodato, L. M., Mraz, R., Baker, S. N. and Graham, S. J., 2007. Haptic Force Feedback Device for Virtual Reality-fMRI Experiments. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, 15(4), pp. 570-576. 16. Enayati, N., De Momi, E. and Ferrigno, G., 2016. Haptics in Robot-Assisted Surgery: Challenges and Benefits. IEEE Reviews in Biomedical Engineering, 9, pp. 49-65. 17. Franken, M., Stramigioli, S., Misra, S., Secchi, C. and Macchelli, A., 2011. Bilateral Telemanipulation with Time Delays: A Two-Layer Approach Combining Passivity and Transparency. In: IEEE Transactions on Robotics, 27(4), pp. 741-756. 18. Guo, S., Liu, Y., Zhang, Y., Zhang, S. and Yamamoto, K., 2016. A VR-Based Self-Rehabilitation System. In: 2016 IEEE International Conference on Mechatronics and Automation, Harbin, pp. 1173-1178. 19. Hace, A. and Jezernik, K., 2010. Bilateral Teleoperation by Sliding Mode Control and Reaction Force Observer. In: IEEE International Symposium on Industrial Electronics, pp. 1809-1816. 20. Hägele, M., Nilsson, K., Pires, N. and Bischoff, R., 2016. Industrial Robotics, 2nd Edition Springer Handbook of Robotics, pp. 1385-1421. 21. Hamid, N. S. S., Aziz, F. A. and Azizi, A., 2017. Virtual Reality Applications in Manufacturing System. In: 2014 Science and Information Conference, London, pp. 1034-1037. 22. Hashtrudi-Zaad, K., and Salcudean, S. E., 2002. Bilateral Parallel Force/Position Teleoperation Control. Journal of Robotic Systems, 19(4), pp. 155–167. 23. Hertkorn, K., Roa, M. A., Brucker, M., Kremer, P. and Borst, C., 2013. Virtual Reality Support for Teleoperation Using Online Grasp Planning. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, pp. 2074-2074. 24. Hjelm, J., 2008. Haptics in Cars. In: Seminar Haptic Communication and Interaction in Mobile Contexts, Dept. of Computer Science, University of Tampere, Finland. 25. Hoshi, T., Abe, D. and Shinoda, H., 2009. Adding Tactile Reaction to Hologram. In: RO-MAN 2009 - 18th IEEE International Symposium on Robot and Human Interactive Communication, Toyama, Japan, pp. 7-11. 26. Hwang, S. and Ryu, J. H., 2010. The Haptic Steering Wheel: Vibro-Tactile Based Navigation for The Driving Environment. In: 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), Mannheim, pp. 660-665. 27. Islam, S., Liu, P. X., Saddik, A. E. and Yang, Y. B., 2015. Bilateral Control of Teleoperation Systems with Time Delay. In: IEEE/ASME Transactions on Mechatronics, 20(1), pp. 1-12. 28. Iwazaki, K., Ohishi, K., Yokokura, Y., Kageyama, K., Takatsu, M. and Urushihara, S., 2014. Robust Sensorless Pressure Control of Electric Injection Moulding Machine using Friction-Free Force Observer. In: Proceedings of the IEEE 13th International Workshop on Advanced Motion Control (AMC), pp. 43-48. 29. Izumikawa, Y., Yubai, K. and Hirai, J., 2005. Fault-Tolerant Control System of Flexible Arm for Sensor Fault by Using Reaction Force Observer. In: IEEE/ASME Transactions on Mechatronics, 10(4), pp. 391-396. 30. Jamaluddin, M. H., Shimono, T. and Motoi, N., 2014. Force-Based Compliance Controller Utilizing Visual Information for Motion Navigation in Haptic Bilateral Control System. IEEJ Journal of Industry Applications, 3(3), pp. 227-235. 31. Katsura, S., Matsumoto, Y. and Ohnishi, K., 2007. Modeling of Force Sensing and Validation of Disturbance Observer for Force Control. In: IEEE Transactions on Industrial Electronics, 54(1), pp. 530-538. 32. Khouja, M. and Offodile, O. F., 1994. The Industrial Robots Selection Problem: Literature Review and Directions for Future Research, IJE Transactions, 26(4), pp. 50-61. 33. Kim, C. H., Kim, S. H., Lee, H. J., Lee, J. K. and Kim, K. H., 2010. A Haptic Device Interface for The Operation of The Virtual Arm. In: International Conference on Control, Automation and Systems (ICCAS), Gyeonggi-do, pp. 1755-1758. 34. Le, K., Dong, Z. and Chuan, L., 2015. A New Maintenance Time Measurement Method by Virtual Reality. Journal of Theoretical and Applied Information Technology (JATIT), 43(1), pp. 74-81. 35. Lee, M. C., Kim, C. Y., Yao, B., Peine, W. J. and Song, Y. E., 2010. Reaction Force Estimation of Surgical Robot Instrument Using Perturbation Observer with SMCSPO Algorithm. In: Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 181-186. 36. Li, C., Wang, D. and Zhang, Y., 2011. iFeel3: A Haptic Device for Virtual Reality Dental Surgery Simulation. In: 2011 International Conference on Virtual Reality and Visualization, Beijing, pp. 179-184. 37. Li, H., Liang, Y., He, T. and Li, Y., 2012. Research on Teleoperation for DFFSR Without Time Delay Based on Virtual Reality. In: Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing, pp. 3611-3616. 38. Luciano, C. J. and Apostoli, R. S., 1997. Virtual Reality Environment for Real Time Simulation, Control and Monitoring of Robotic Manufacturing Flexible Systems. In: Advanced Robotics, ICAR Proceedings, 8th International Conference, Monterey, Canada, pp. 673-680. 39. Maclean, K. E. and Hayward, V., 2008. Do It Yourself Haptics: Part II [Tutorial]. IEEE Robotics and Automation Magazine, 15(1), pp. 104-119. 40. Mansor, N. N., Jamaluddin, M. H. and Shukor, A. Z., 2017. Concept and Application of Virtual Reality Haptic Technology: A Review, Journal of Theoretical and Applied Information Technology (JATIT), 95(14), pp. 3320-3336. 41. Mansor, N. N., Jamaluddin, M. H. and Shukor, A. Z., 2018. A Study of Accuracy and Time Delay for Bilateral Master-Slave Industrial Robotic Arm Manipulator System, MATEC Web of Conferences, EDP Sciences, 150, pp. 1-7. 42. Mauricio, O. C., Israel, Z. R. and Jesús, P. C., 2014. Language Interpreter for The Deaf Core Using a Virtual Reality Data-Glove. Journal of Theoretical and Applied Information Technology (JATIT), 33(2), pp. 135-141. 43. McMahan, W., Romano, J. M., Rahuman, A. M. A. and Kuchenbecker, K. J., 2010. High Frequency Acceleration Feedback Significantly Increases the Realism of Haptically Rendered Textured Surfaces. In: 2010 IEEE Haptics Symposium, Waltham, pp. 141-148. 44. Mihelj, M. and Podobnik, J., 2012. Haptics for Virtual Reality and Teleoperation: Human Haptic System. Intelligent Systems, Control and Automation: Science and Engineering, 64, Netherlands: Springer Science and Business Media, pp. 41-55. 45. Mohammadi, A., Tavakoli, M., Marquez, H. J. and Hashemzadeh, F., 2013. Nonlinear disturbance observer design for robotic manipulators, Control Engineering Practice, 21(3), pp. 253-267. 46. Mohareri, O., Schneider, C. and Salcudean, S., 2014. Bimanual Telerobotic Surgery with Asymmetric Force Feedback: A Davinci® Surgical System Implementation. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, pp. 4272-4277. 47. Mostefa, M., Boudadi, L. K. E., Loukil, A., Mohamed, K. and Amine, D., 2015. Design of Mobile Robot Teleoperation System Based on Virtual Reality. In: 2015 3rd International Conference on Control, Engineering and Information Technology (CEIT), Tlemcen, pp. 1-6. 48. Mousavi, M. and Aziz, F. A., 2008. State of The Art of Haptic Feedback in Virtual Reality in Manufacturing. In: 2008 International Symposium on Information Technology, Kuala Lumpur, Malaysia, pp. 1-7. 49. Nahavandil, S. and Preece, C., 1994. A Virtual Manufacturing Environment with an Element of Reality. In: Fourth International Conference on Factory 2000 - Advanced Factory Automation, pp. 624-629. 50. Nof, S. Y., Knight Jr., J. L. and Salvendy, G., 1980. Effective Utilization of Industrial Robots - A Job and Skills Analysis Approach. In: AIIE Transactions, 12(3), pp. 216-225. 51. Nozaki, T., Mizoguchi, T. and Ohnishi, K., 2014. Decoupling Strategy for Position and Force Control Based on Modal Space Disturbance Observer. In: IEEE Transactions on Industrial Electronics, 61(2), pp. 1022-1032. 52. Nurung, S. and Nilkhamhang, I., 2010. A Robust Adaptive Algorithm for Bilateral Control System without Force Sensor with Time Delay. In: Proceedings of the SICE Annual Conference, pp. 678-683. 53. Ohba, Y., Sazawa, M., Ohishi, K., Asai, T., Majima, K., Yoshizawa, Y. and Kageyama, K., 2009. Sensorless Force Control for Injection Moulding Machine Using Reaction Torque Observer. In: IEEE Transactions on Industrial Electronics, 56(8), pp. 2955-2960. 54. Ohishi, K., Ohnishi, K. and Miyachi, K., 1983. Torque-Speed Regulation Od DC-Motor Based on Load Torque Estimation Method. In: Proceedings of IPEC-Tokyo, pp. 1209-1218. 55. Petermeijer, S. M., Abbink, D. A., Mulder, M. and De Winter, J. C. F., 2015. The Effect of Haptic Support Systems on Driver Performance: A Literature Survey. In: IEEE Transactions on Haptics, 8(4), pp. 467-479. 56. Pires, L. A., Serpa, Y. A. and Rodrigues, M. A. F., 2016. SimImplanto - A Virtual Dental Implant Training Simulator. In: 2016 XVIII Symposium on Virtual and Augmented Reality (SVR), Gramado, pp. 193-197. 57. Podobnik, J. and Mihelj, M., 2012. Haptics for Virtual Reality and Teleoperation: Introduction to Virtual Reality. Intelligent Systems, Control and Automation: Science and Engineering, Vol. 64. Netherlands: Springer Science and Business Media, pp. 1-33. 58. Polushin, I. G., Rhinelander, J. P., Liu, P. X. and Lung, C. H., 2009. Virtual Reality Enhanced Bilateral Teleoperation with Communication Constraints. In: Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, pp. 2088-2093. 59. Popescu, N., Ivanescu, M. and Popescu, D., 2013. Force Observer-Based Control for a Rehabilitation Hand Exoskeleton System. In: Proceedings of the 9th Asian Control Conference, pp. 1-6. 60. Ratiu, M. and Prichici, M., 2017. Industrial Robot Trajectory Optimization - A Review, MATEC Web of Conferences, EDP Sciences, 126, pp. 1-6. 61. Ravikanth, D., Mishra, M. and Hariharan, P., 2015. Review on Haptics Technology and Its Modeling , Rendering and Future Applications on Texture Identification. In: 2015 International Conference on Man and Machine Interfacing (MAMI), Bhubaneswar, pp. 1-6. 62. Regenbrecht, J., Tavakkoli, A. and Loffredo, D., 2017. A Robust and Intuitive 3D Interface for Teleoperation of Autonomous Robotic Agents Through Immersive Virtual Reality Environments. In: IEEE Symposium on 3D User Interfaces (3DUI), Los Angeles, California, pp. 199-200. 63. Ren, T. J. and Chen, T. C., 2007. Modeling and Control of a Power-Assisted Mobile Vehicle Based on Torque Observer. IET Control Theory and Applications, 1(5), pp. 1405-1412. 64. Rizzi, S. H., Banerjee, P. P. and Luciano, C. J., 2007. Automating the Extraction of 3D Models from Medical Images for Virtual Reality and Haptic Simulations. In: 2007 IEEE International Conference on Automation Science and Engineering, Scottsdale, Arizona, pp. 152-157. 65. Rosen, J., Hannaford, B., Richards, C. G. and Sinanan, M. N., 2001. Markov Modeling of Minimally Invasive Surgery Based on Tool/Tissue Interaction and Force/Torque Signatures for Evaluating Surgical Skills. In: IEEE Transactions on Biomedical Engineering, 48(5), pp. 579-591. 66. Saddik, A. E., 2007. The Potential of Haptics Technologies. IEEE Instrumentation and Measurement Magazine, vol. 10, no. 1, pp. 10-17. 67. Saddik, A. E., Orozco, M., Eid, M. and Cha, J., 2011. Haptics Technologies: Computer Haptics. Springer Series on Touch and Haptics Systems, Berlin Heidelberg: Springer-Verlag, pp. 105-143. 68. Sadhu, S. and Ghoshal, T. K., 2011. Sight Line Rate Estimation in Missile Seeker Using Disturbance Observer-Based Technique. In: IEEE Transactions on Control Systems Technology, 19(2), pp. 449-454. 69. Sansanayuth, T., Nilkhamhang, I. and Tungpimolrat, K., 2012. Teleoperation with Inverse Dynamics Control for Phantom Omni Haptic Device. In: 2012 Proceedings of SICE Annual Conference (SICE), Akita, Japan, pp. 2121-2126. 70. Sariyildiz, E. and Ohnishi, K., 2014. A Comparison Study for Force Sensor and Reaction Force Observer based Robust Force Control Systems. In: Proceedings of the IEEE 23rd International Conference on Industrial Electronics, pp. 1156-1161. 71. Sariyildiz, E. and Ohnishi, K., 2014. A Guide to Design Disturbance Observer based Motion Control Systems. In: Proceedings of International Power Electronics Conference, pp. 2483-2488. 72. Sariyildiz, E. and Ohnishi, K., 2015. An Adaptive Reaction Force Observer Design. In: IEEE/ASME Transactions on Mechatronics, 20(2), pp. 750-760. 73. Serrano, C. V., Bonilla, I., Gómez, F. V. and Mendoza, M., 2015. Development of A Haptic Interface for Motor Rehabilitation Therapy Using Augmented Reality. In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, pp. 1156-1159. 74. Shanker, K. and Ghosh, A., 1989. Flexible Automation and Robotics in Manufacturing, IETE Journal of Research, 35(4), pp. 187-197. 75. Shimono, T., Jamaluddin, M. H. and Motoi, N., 2013. Object Follow-up Control Based on Visual Feedback in Remote Control System. In: IEEJ Joint Technical Meeting on Industrial Instrumentation and Control (IIC), pp. 45-46. 76. Shimono, T., Katsura, S. and Ohnishi, K., 2007. Abstraction and Reproduction of Force Sensation from Real Environment by Bilateral Control. In: IEEE Transactions on Industrial Electronics, 54(2), pp. 907-918. 77. Shimono, T., Nezu, K. and Aboshi, M., 2010. Variable Contact Force Control based on Reaction Force Control with Adjustment Ratio. In: Proceedings of the IEEE International Power Electronics Conference, 2, pp. 2545-2550. 78. Siciliano, B. and Khatib, O., 2008. Haptics in Springer Handbook of Robotics, Germany: Springer, pp. 719-739. 79. Smuts, J. F., 2011. Process Control for Practitioners, United State of America: OptiControls Inc. 80. Soygüder, S. and Abut, T., 2016. Haptic Industrial Robot Control with Variable Time Delayed Bilateral Teleoperation. Industrial Robot, 43, pp. 390-402. 81. Srinivasan, M. A., 1995. What is Haptics? Lab. Human Machine Haptics Touch Lab, MIT, pp. 1–11. 82. Stone, R. J., 2011. The (Human) Science of Medical Virtual Learning Environments. Philosophy Transition of the Royal Society of London B: Biological Sciences, 366(1562), pp. 276-285. 83. Suzuki, A. and Ohnishi, K., 2013. Novel Four-Channel Bilateral Control Design for Haptic Communication Under Time Delay Based on Modal Space Analysis. In: IEEE Transactions on Control Systems Technology, 21(3), pp. 882-890. 84. Talaba, D., Antonya, C., Stavar, A. and Georgescu, V. C., 2011. Virtual Reality in Product Design and Robotics. In: 2nd International Conference on Cognitive Infocommunications (CogInfoCom), Budapest, pp. 1-6. 85. Tanaka, H., Ohnishi, K., Nishi, H., Kawai, T., Morikawa, Y., Ozawa, S. and Furukawa, T., 2009. Implementation of Bilateral Control System Based on Acceleration Control Using FPGA for Multi-DoF Haptic Endoscopic Surgery Robot. In: IEEE Transactions on Industrial Electronics, 56(3), pp. 618-627. 86. Tang, X., Zhao, D., Yamada, H. and Ni, T., 2009. Haptic Interaction in Teleoperation Control System of Construction Robot Based on Virtual Reality. In: 2009 International Conference on Mechatronics and Automation, Changchun, pp. 78-83. 87. Tian, D., Yashiro, D. and Ohnishi, K., 2012. Wireless Haptic Communication Under Varying Delay by Switching-Channel Bilateral Control with Energy Monitor. In: IEEE/ASME Transactions on Mechatronics, 17(3), pp. 488-498. 88. Tokuyama, Y., Rajapakse, R. P. C. J., Miya, S. and Konno, K., 2016. Development of a Whack-a-Mole Game with Haptic Feedback for Rehabilitation. In: 2016 Nicograph International (NicoInt), Hanzhou, pp. 29-35. 89. Townsend, W. T., 2000. The Barretthand Grasper-Programmably Flexible Part Handling and Assembly MCB Industrial Robot. Feature Article Industrial Robot: An International Journal, 27(3), pp. 181-188. 90. Wallach, W. and Allen, C., 2009. Moral Machines Teaching Robots Right from Wrong, Oxford University Press, Inc. 91. Wang, W., Song, G., Nonami, K., Hirata, M. and Miyazawa, O., 2006. Autonomous Control for Micro-Flying Robot and Small Wireless Helicopter X.R.B, In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, pp. 2906-2911. 92. Wei, Z., Sheng, Q. Y., Chaozhi, X. and Wu-shuai, G., 2011. The Application of Virtual Reality Technology in Platen Die-Cutting Machine Design-Manufacturing. In: InternationalConference on Advanced Technology of Design and Manufacture (ATDM 2011), Changzhou, China, pp. 1-5. 93. Xu, J. and Gong, Q., 2008. Research on Technology Development Actuality of The Virtual Reality Applied to Design and Manufacturing Processes. In: 2008 9th International Conference on Computer-Aided Industrial Design and Conceptual Design, Kunming, pp. 307-312. 94. Xu, W. and Lv, C., 2011. Research of Virtual Reality in Industrial Design Manufacture and Performance Testing. In: 2011 2nd International Conference on Intelligent Control and Information Processing, Harbin, pp. 403-405. 95. Zhong, G., Kobayashi, Y., Hoshino, Y. and Emaru, T., 2012. Intuitive Teleoperation of Nonholonomic Mobile Robot with A Manipulator Based on Virtual Reality and Wi-Fi. In: IET International Conference on Information Science and Control Engineering 2012 (ICISCE 2012), Shenzhen, pp. 1-5.