|4/2011 - 3|
Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIENDRISTIC-DURRANT, D. , GRIGORESCU, S. M. , GRASER, A. , COJBASIC, Z. , NIKOLIC, V.
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robust robot vision, feedback control in image processing, feature-based object recognition, neuro-fuzzy classification, assistive robot
vision(8), systems(8), object(7), robots(6), robotics(6), graeser(6), system(5), robot(5), autonomous(5), robotic(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 15 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04003
Web of Science Accession Number: 000297764500003
SCOPUS ID: 84856594148
A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method.
|References|||||Cited By «-- Click to see who has cited this paper|
| D. Kim, R. Lovelett, A. Behal, "An empirical study with simulated adl tasks using vision-guided assistive robot arm", in Proc. of the IEEE 11th Int. Conf. on Rehabilitation Robotics ICORR, Japan, 2009. |
[CrossRef] [SCOPUS Times Cited 16]
 D. Kragic, H. I. Christensen, "Advances in robot vision", Robotics and Autonomous Systems, vol. 52, pp. 1-3, 2005.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 18]
 S. Hussmann and T. Liepert, "Robot Vision System based on a 3D-TOF Camera", Instrumentation and Measurement Technology Conference-IMTC 2007, Warsaw, Poland, 2007.
 S. Gaechter, A. Harati and R. Siegwart, "Incremental Object Part Detection toward Object Classification in a Sequence of Noisy Range Images", in Proc. of IEEE International Conference on Robotics and Automation ICRA 2008, 2008.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 10]
 G. Mester, A. Rodic, Autonomous Locomotion of Humanoid Robots in Presence of Mobile and Immobile Obstacles, Towards Intelligent Engineering and Information Technology, Studies in Computational Intelligence, Volume 243, 2009.
[CrossRef] [SCOPUS Times Cited 1]
 T. Asfour, P. Azad, N. Vahrenkamp, K. Regenstein, A. Bierbaum, K. Welke, J. Schroder, R. Dillmann, Toward humanoid manipulation in human-centered environments, Robotics and Autonomous Systems, vol. 56, no. 1, pp. 54-65, 2008.
[CrossRef] [Web of Science Times Cited 67] [SCOPUS Times Cited 86]
 D. G. Lowe, "Distinctive image features from scale-invariant keypoints", Int. Journal of Computer Vision, vol. 60, no. 2, 2004.
[CrossRef] [SCOPUS Times Cited 31998]
 D. Kragic, Bjoerman, H. Christensen, J.-O. Eklundh, "Vision for robotic object manipulation in domestic settings", Robotics and Autonomous Systems, vol. 52, pp. 85-100, 2005.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 62]
 M. Sridharan, P. Stone, "Structure-based color learning on a mobile robot under changing illumination", Autonomous Robots Journal, vol. 23, pp. 161-182, 2007.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 11]
 O. Ivlev, C. Martens, A. Graeser, "Rehabilitation robots FRIEND-I and FRIEND-II with the dexterous lightweight manipulator", Restoration of Wheeled Mobility in SCI Rehabilitation, vol. 17, pp. 111-123, 2005.
 O. Prenzel, C. Martens, M. Cyriacks, C. Wang, A. Graeser, "System controlled user interaction within the service robotic control architecture MASSiVE", Robotica, Special Issue, vol. 25, no. 2, 2007.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 13]
 D. Ojdanic, A. Graeser, "Improving the trajectory quality of a 7 DoF manipulator", in Proc. of the Robotik Conf., Munich, Germany, 2008.
 S. K. Vuppala, S. M. Grigorescu, D. Ristic-Durrant, A. Graeser, "Robust color object recognition for a service robotic task in the system FRIEND II", in Proc. of the IEEE 10th Int. Conf. on Rehabilitation Robotics ICORR, Noordwijk, Netherlands, 2007.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 10]
 P. Melin, O. Castillo, Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing, Springer-Verlag, 2005.
 P. Sanz, M. R., J. Sanchez, "Including efficient object recognition capabilities in online robots: From a statistical to a neural-network classifier", IEEE Trans. on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 35, no. 1, pp. 87-96, 2005.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 11]
 R. Jang, C-T. Sun, E. Mizutani, Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice Hall, 1997.
 E. Dogantekin, M. Yilmaz, A. Dogantekin, E. Avci, A. Sengur, "A robust technique based on invariant moments - ANFIS for recognition of human parasite eggs in microscopic images", Expert Systems with Applications, vol. 35, no. 3, pp. 728-738, 2008.
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 34]
 R. Hartley, A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2004.
 S. K. Vuppala, A. Graeser, "An approach for tracking the 3d object pose using two object points", in Proc. of the Int. Conf. on Vision Systems ICVS, Santorini, Greece, 2008.
[CrossRef] [SCOPUS Record]
 D. Ristic, Feedback structures in image processing, Ph.D. thesis, Shaker Verlag, Germany, 2007.
 D. Ristic, A. Graser, "Performance measure as feedback variable in image processing", EURASIP Journal on Applied Signal Processing, vol. 2006, 2006.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 9]
 S. M. Grigorescu, D. Ristic-Durrant, A. Graeser, "ROVIS: Robust machine Vision for Service robotic system FRIEND", in Proc. of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, USA, October, 2009.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 16]
 M. Sridharan, "Bootstrap Learning and Visual Processing Management on Mobile Robots", Advances in Artificial Intelligence, vol. 2010, 2010.
 C. Suliman, C. Cruceru, F. Moldoveanu, "Kalman filter based tracking in an video surveillance system", Advances in Electrical and Computer Engineering, vol. 10, no. 2, pp. 30-34, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]
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