A Target Grabbing Strategy for Telerobot Based on Improved Stiffness Display Device

Pengwen Xiong; Xiaodong Zhu; Aiguo Song; Lingyan Hu; Xiaoping P. Liu; Lihang Feng

doi:10.1109/JAS.2016.7510256

Volume 4 Issue 4

Oct. 2017

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 15.3, Top 1 (SCI Q1)

CiteScore: 23.5, Top 2% (Q1)
Google Scholar h5-index: 77， TOP 5

Turn off MathJax

Article Contents

Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2017 > 4(4): 661-667

Pengwen Xiong, Xiaodong Zhu, Aiguo Song, Lingyan Hu, Xiaoping P. Liu and Lihang Feng, "A Target Grabbing Strategy for Telerobot Based on Improved Stiffness Display Device," IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 661-667, Oct. 2017. doi: 10.1109/JAS.2016.7510256

Citation:

Pengwen Xiong, Xiaodong Zhu, Aiguo Song, Lingyan Hu, Xiaoping P. Liu and Lihang Feng, "A Target Grabbing Strategy for Telerobot Based on Improved Stiffness Display Device," IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 661-667, Oct. 2017. doi: 10.1109/JAS.2016.7510256

Citation:

PDF( 8409 KB)

A Target Grabbing Strategy for Telerobot Based on Improved Stiffness Display Device

doi: 10.1109/JAS.2016.7510256

Pengwen Xiong^{1, 2
,},
Xiaodong Zhu^1
,,
Aiguo Song^2
,,
Lingyan Hu^{1
,
,},
Xiaoping P. Liu^{1, 3
,},
Lihang Feng^4
,

1.
School of Information Engineering, Nanchang University, Nanchang 330031, China
2.
School of Instrumentation Science and Engineering, Southeast University, Nanjing 210096, China
3.
Department of Systems and Computer Engineering, Carleton University, Ottawa, ONK1 S5B6, Canada
4.
Computer Integrated Surgical Systems and Technology Engineering Research Center(CISST ERC), Johns Hopkins University, Baltimore, MD 21218, USA

Funds:

the National Natural Science Foundation of China 61663027

the National Natural Science Foundation of China 61325018

the National Natural Science Foundation of China 81501560

the Science and Technology Department of Jiangxi Province of China 20151BAB207050

More Information

Author Bio:
Pengwen Xiong received the B.S. degree from North University of China in 2009, and Ph.D. degree in instrumentation science and technology from Southeast University, China, in 2015. He visited Laboratory for Computational Sensing and Robotics, Johns Hopkins University from 2013 to 2014. He is currently a lecturer at the School of Information Engineering, Nanchang University. His research interests include human robot interaction, robotic sensing and controlling, (e-mail: steven.xpw@ncu.edu.cn)

Xiaodong Zhu received the B.S. degree in automation from Nanchang University in 2016, and is currently a master student in control engineering at the School of Information Engineering, Nanchang University. His research interests include human robot interaction, computer simulation and data analysis, (e-mail: xiaohd@ e-mail.ncu.edu.cn)

Aiguo Song received the B.S. degree in automatic control in 1990, the M.S. degree in measurement and control in 1993 from Nanjing Aeronautics and Astronautics University, Nanjing, China, and the Ph.D. degree in measurement and control from Southeast University, Nanjing, in 1996. From April 2003 to April 2004, he was a Visiting Scientist with the Lab for Intelligent Mechanical Systems, Northwestern University, Evanston, IL, USA. He is currently a Professor with the Department of Instrumentation Science and Engineering, Southeast University. His current research interests include haptic display and teleoperation robot, (e-mail: a.g.song@seu.edu.cn)

Lingyan Hu received the Ph.D. degree from Nanchang University in 2011. She is currently a Professor in School of Information Engineering, Nanchang University, Nanchang, China. Her current research interests include teleoperation systems, haptic control and virtual surgery system, (e-mail: hulingyan@ncu.edu.cn)

Xiaoping P. Liu received the B.Sc. and M.Sc. degrees from Northern Jiaotong University, Beijing, China, in 1992 and 1995, respectively, and the Ph.D. degree from the University of Alberta, Edmonton, AB, Canada, in 2002. He is currently a Canada Research Chair Professor with the Department of Systems and Computer Engineering, Faculty of Engineering and Design, Carleton University, Ottawa, ON, Canada. His research interests include interactive networked systems and teleoperation, robotics, intelligent systems, haptics, micromanipulation, context-aware intelligent networks, and their applications to biomedical engineering, (e-mail: xpliu@sce.carleton.ca)

Lihang Feng received the B.S. degree in flight vehicle design and engineering from Nanjing University of Aeronautics and Astronautics, China, 2009. He is currently a visiting Ph.D student in Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA. He is also a Ph.D candidate in instrumentation science and technology, Southeast University, China. His research interests include sensing technology, robotics design and modeling, (e-mail: lfeng8@jhu.edu)
Corresponding author: Lingyan Hu, e-mail:hulingyan@ncu.edu.cn
Received Date: 2016-05-31
Accepted Date: 2016-10-26

Abstract

Abstract

Most target grabbing problems have been dealt with by computer vision system, however, computer vision method is not always enough when it comes to the precision contact grabbing problems during the teleoperation process, and need to be combined with the stiffness display to provide more effective information to the operator on the remote side. Therefore, in this paper a more portable stiffness display device with a small volume and extended function is developed based on our previous work. A new static load calibration of the improved stiffness display device is performed to detect its accuracy, and the relationship between the stiffness and the position is given. An effective target grabbing strategy is presented to help operator on the remote side to judge and control and the target is classified by multi-class SVM (supporter vector machine). The teleoperation system is established to test and verify the feasibility. A special experiment is designed and the results demonstrate that the improved stiffness display device could greatly help operator on the remote side control the telerobot to grab target and the target grabbing strategy is effective.
- Multi-class SVM (supporter vector machine),
- teleoperation,
- target grabbing,
- stiffness display

FullText(HTML)

References(29)

References

[1]	P. Dario, B. Hannaford, and A. Menciassi, "Smart surgical tools and augmenting devices, " IEEE Trans. Rob. Automat. , vol. 19, no. 5, pp. 782-792, Oct. 2003. http: //ieeexplore. ieee. org/xpls/icp. jsp?arnumber=1236751
[2]	H. J. Li and A. G. Song, "Virtual-environment modeling and correction for force-reflecting teleoperation with time delay, " IEEE Trans. Ind. Electron. , vol. 54, no. 2, pp. 1227-1233, Apr. 2007. http: //ieeexplore. ieee. org/document/4140627/
[3]	W. Qin, Z. X. Liu, and Z. Q. Chen, " Formation control for nonlinear multi-agent systems with linear extended state observer, " IEEE/CAA J. Automat. Sin. , vol. 1, no. 2, pp. 171-179, Apr. 2014. http: //ieeexplore. ieee. org/document/7004547/
[4]	Y. N. Yang, C. C. Hua, and X. P. Guan, "Finite time control design for bilateral teleoperation system with position synchronization error constrained, " IEEE Trans. Cybern. , vol. 46, no. 3, pp. 609-619, Mar. 2015. http: //www. ncbi. nlm. nih. gov/pubmed/25823053
[5]	C. C. Hua, Y. N. Yang, and P. X. Liu, "Output-Feedback adaptive control of networked teleoperation system with time-varying delay and bounded inputs, " IEEE/ASME Trans. Mechatron. , vol. 20, no. 5, pp. 2009-2020, Oct. 2015. http: //ieeexplore. ieee. org/document/6923461/
[6]	Y. N. Yang, C. C. Hua, and X. P. Guan, "Adaptive fuzzy finite-time coordination control for networked nonlinear bilateral teleoperation system, " IEEE Trans. Fuzzy Syst. , vol. 22, no. 3, pp. 631-641, Jun. 2014. http: //ieeexplore. ieee. org/document/6542671/
[7]	Y. N. Yang, C. C. Hua, and X. P. Guan, "Finite-time synchronization control for bilateral teleoperation under communication delays, " Robot. Comput. Integr. Manuf. , vol. 31, pp. 61-69, Feb. 2015. http: //ieeexplore. ieee. org/document/5196767/
[8]	L. Z. Pan, A. G. Song, G. Z. Xu, H. J. Li, H. Zeng, and B. G. Xu, "Safety supervisory strategy for an upper-limb rehabilitation robot based on impedance control, " Int. J. Adv. Rob. Syst. , vol. 10, no. 2, pp. 127, Feb. 2013. doi: 10. 5772/55094
[9]	A. Bicchi, E. P. Scilingo, and D. De Rossi, "Haptic discrimination of softness in teleoperation: The role of the contact area spread rate, " IEEE Trans. Rob. Automat. , vol. 16, no. 5, pp. 496-504, Oct. 2000. http: //ieeexplore. ieee. org/xpls/abs_all. jsp?arnumber=880800
[10]	S. Aiguo, L. Jia, and W. Juan, "Softness haptic display device for human-computer interaction, " Int. J. Adv. Rob. Syst. , vol. 5, pp. 257-278, 2008. doi: 10. 5772/6299
[11]	X. Wang, N. D. Georganas, and E. M. Petriu, "Fabric texture analysis using computer vision techniques, " IEEE Trans. Instrum. Meas. , vol. 60, no. 1, pp. 44-56, Jan. 2011. http: //ieeexplore. ieee. org/document/5565463/
[12]	D. Copeland and J. Finlay, "Identification of the optimum resolution specification for a haptic graphic display, " Interact. Comput. , vol. 22, no. 2, pp. 98-106, Mar. 2010. http: //dl. acm. org/citation. cfm?id=1747021
[13]	J. Wu, L. Y. Li, R. Q. Yan, D. J. Ni, and W. Liu, "Experimental study on virtual texture force perception using the JND method, " Int. J. Adv. Rob. Syst. , vol. 9, pp. 63, Jun. 2012. doi: 10. 5772/50533
[14]	A. Oonsivilai and N. Meeboon, "Silk texture defect recognition system using computer vision and artificial neural networks, " in Proc. 2nd International Congress on Image and Signal Processing, Tianjin, China, 2009, 1-4. http: //ieeexplore. ieee. org/xpl/abstractAuthors. jsp?reload=true & arnumber=5303972
[15]	H. Fujimoto, L. C. Zhu, and K. Abdel-Malek, "Image-based visual servoing for grasping unknown objects, " in Proc. 26th Annu. Confjerence of the IEEE Industrial Electronics Society, Nagoya, Japan, vol. 2, pp. 876-881, 2000. http: //ieeexplore. ieee. org/xpls/abs_all. jsp?arnumber=972238
[16]	M. Trabelsi, N. Aitoufroukh, and S. Lelandais, "Improvements of object grabbing method by using color images and neural networks classification, " in Proc. 32nd Conf. IEEE Industrial Electronics, Paris, France, 2006, pp. 3922-3927. http: //ieeexplore. ieee. org/xpls/icp. jsp?arnumber=4153469
[17]	L. Bodenhagen, D. Kraft, and P. E. Hotz, "Learning to grasp unknown objects based on 3D edge information, " in Proc. 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation, Daejeon, Korea, 2009, pp. 421-428. http: //ieeexplore. ieee. org/xpls/icp. jsp?arnumber=5423169
[18]	S. P. DiMaio and S. E. Salcudean, "Needle insertion modeling and simulation, " IEEE Trans. Rob. Autom. , vol. 19, no. 5, pp. 864-875, Oct. 2003. http: //ieeexplore. ieee. org/xpls/icp. jsp?arnumber=1236759
[19]	T. H. Massie and J. K. Salisbury, "The PHANToM haptic interface: A device for probing virtual objects, " in Proc. ASME Winter Annu. Meeting: Dyn. Syst. and Contr. , vol. 55, pp. 295-300, 1994. http: //ci. nii. ac. jp/naid/10012640353
[20]	G. C. Burdea, "Haptics issues in virtual environments, " in Proc. Computer Graphics International, Geneva, Switzerland, 2000, pp. 295-302. http: //dl. acm. org/citation. cfm?id=793058
[21]	Y. Guo, A. G. Song, J. T. Bao, H. R. Tang, and J. W. Cui, "A combination of terrain prediction and correction for search and rescue robot autonomous navigation, " Int. J. Adv. Rob. Syst. , vol. 6, no. 3, pp. 207-214, Sep. 2009. http: //www. oalib. com/paper/2577101
[22]	C. W. Hsu and C. J. Lin, "A comparison of methods for multiclass support vector machines, " IEEE Trans. Neural Netw. , vol. 13, no. 2, pp. 415-425, Mar. 2002. http: //www. ncbi. nlm. nih. gov/pubmed?cmd=Retrieve & list_uids=18244442 & dopt=Abstract
[23]	K. Englehart, B. Hudgin, and P. A. Parker, "A wavelet-based continuous classification scheme for multifunction myoelectric control, " IEEE Trans. Biomed. Eng. , vol. 48, no. 3, pp. 302-311, Mar. 2001. http: //www. ncbi. nlm. nih. gov/pubmed/11327498
[24]	C. J. C. Burges, "A tutorial on support vector machines for pattern recognition, " Data Min. Knowl. Discov. , vol. 2, no. 2, pp. 121-167, Jun. 1998. http: //dl. acm. org/citation. cfm?id=593463 & CFID=448038169 & CFTOKEN=58479656
[25]	M. A. Hearst, S. T. Dumais, E. Osuna, J. Platt, and B. Scholkopf, "Support vector machines, " IEEE Intell. Syst. Their Appl. , vol. 13, no. 4, pp. 18-21, Jul. -Aug. 1998. http: //ieeexplore. ieee. org/xpls/abs_all. jsp?arnumber=708428
[26]	O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee, "Choosing multiple parameters for support vector machines, " Mach. Learn. , vol. 46, no. 1-3, pp. 131-159, Jan. 2002. doi: 10. 1023/A%3A1012450327387
[27]	C. Huang, L. S. Davis, and J. R. G. Townshend, "An assessment of support vector machines for land cover classification, " Int. J. Remote Sens. , vol. 23, no. 4, pp. 725-749, Feb. 2002. http: //ci. nii. ac. jp/naid/80015545139
[28]	C. H. Q. Ding and I. Dubchak, "Multi-class protein fold recognition using support vector machines and neural networks, " Bioinformatics, vol. 17, no. 4, pp. 349-358, Apr. 2001. http: //www. ncbi. nlm. nih. gov/pubmed/11301304
[29]	G. M. Foody and A. Mathur, "A relative evaluation of multiclass image classification by support vector machines, " IEEE Trans. Geosci. Remote Sens. , vol. 42, no. 6, pp. 1335-1343, Jun. 2004. http: //ieeexplore. ieee. org/xpls/icp. jsp?arnumber=1304900

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(11)

Get Citation

PDF

XML

Article Metrics

Article views (1320) PDF downloads(121)

A Target Grabbing Strategy for Telerobot Based on Improved Stiffness Display Device

doi: 10.1109/JAS.2016.7510256

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Export File

Citation

Format

Content