|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.
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (574 KB) | Citation | Downloads: 1,123 | Views: 3,766|
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 18]
 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 17] [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.
[CrossRef] [SCOPUS Times Cited 23]
 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 5] [SCOPUS Times Cited 11]
 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 2]
 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 75] [SCOPUS Times Cited 96]
 D. G. Lowe, "Distinctive image features from scale-invariant keypoints", Int. Journal of Computer Vision, vol. 60, no. 2, 2004.
[CrossRef] [Web of Science Times Cited 25810] [SCOPUS Times Cited 36398]
 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 54] [SCOPUS Times Cited 68]
 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 7] [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 4] [SCOPUS Times Cited 11]
 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 27] [SCOPUS Times Cited 40]
 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 2] [SCOPUS Times Cited 10]
 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 5] [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 9] [SCOPUS Times Cited 12]
Web of Science® Citations for all references: 26,029 TCR
SCOPUS® Citations for all references: 36,758 TCR
Web of Science® Average Citations per reference: 1,085 ACR
SCOPUS® Average Citations per reference: 1,532 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2020-07-13 21:47 in 134 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.