Abstract
Recent advances in mechanical and electronic engineering led to the building of more sophisticated mechatronic systems excelling in simplicity, reliability and versatility. On the contrary, the complexity of their parts necessitate integrated control systems along with advanced visual feedback. Generally, a vision system aims at bridging the gap between humans and machines in terms of providing to the latter information about what is perceived visually. This paper shows how the vision system of an advanced mechatronic framework named ACROBOTER is used for the localization of objects. ACROBOTER develops a new locomotion technology that can effectively be utilized in a workplace environment for manipulating small objects simultaneously. Its vision system is based on a multi-camera framework that is responsible for both finding patterns and providing their location in the 3D working space. Moreover, this work presents a novel method for recognizing objects in a scene and providing their spatial information.
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References
Kouskouridas, R., Kyriakoulis, N., Chrysostomou, D., Belagiannis, V., Mouroutsos, S., Gasteratos, A.: The Vision System of the ACROBOTER Project. In: International Confernce on Intelligent Robotics and Applications, pp. 957–966 (2009)
Kouskouridas, R., Badekas, E., Gasteratos, A.: Simultaneous Visual Object Recognition and Position Estimation Using SIFT. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds.) ICIRA 2009. LNCS, vol. 5928, pp. 866–875. Springer, Heidelberg (2009)
Balaguer, C., Gimenez, A., Huete, A., Sabatini, A., Topping, M., Bolmsjo, G.: The MATS robot: service climbing robot for personal assistance. IEEE Robotics & Automation Magazine 13(1), 51–58 (2006)
Sato, T., Fukui, R., Morishita, H., Mori, T.: Construction of ceiling adsorbed mobile robots platform utilizing permanent magnet inductive traction method. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2004, vol. 1 (2004)
Vaish, V., Levoy, M., Szeliski, R., Zitnick, C., Kang, S.: Reconstructing occluded surfaces using synthetic apertures: Stereo, focus and robust measures. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2 (2006)
Zhang, J., McMillan, L., Yu, J., Hill, U.: Robust tracking and stereo matching under variable illumination. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1 (2006)
Zwicker, M., Vetro, A., Yea, S., Matusik, W., Pfister, H., Durand, F.: Resampling, antialiasing, and compression in multiview 3-D displays. IEEE Signal Processing Magazine 24(6), 88–96 (2007)
Schweighofer, G.: Robust pose estimation from a planar target. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 2024–2030 (2006)
Chandraker, M., Stock, C., Pinz, A.: Real-time camera pose in a room. In: Crowley, J.L., et al. (eds.) ICVS 2003. LNCS, vol. 2626, pp. 98–110. Springer, Heidelberg (2003)
Xu, D., Li, Y.F.: A new pose estimation method based on inertial and visual sensors for autonomous robots. In: IEEE International Conference on Robotics and Biomimetics, Sanya, China, pp. 405–410 (2007)
Torralba, A., Oliva, A.: Depth estimation from image structure. IEEE Trans. Pattern Anal. Mach. Intell., 1226–1238 (2002)
Naplapntidis, L., Sirakoulis, G., Gasteratos, A.: Review of stereo vision algorithms: from software to hardware. International Journal of Optomechatronics 2(4), 435–462 (2008)
Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, USA, pp. 2161–2168 (2006)
Sivic, J., Zisserman, A.: Video google: a text retrieval approach to object matching in videos. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, Nice, France, pp. 1470–1477 (2003)
Liao, M., Wei, L., Chen, W.: A novel affine invariant feature extraction for optical recognition, vol. 3, pp. 1769–1773 (August 2007)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (surf). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Gool, L.V.: A comparison of affine region detectors. Int. J. Comput. Vision 65(1-2), 43–72 (2005)
Mikolajczyk, K., Schmid, C.: Scale & affine invariant interest point detectors. Int. J. Comput. Vision 60(1), 63–86 (2004)
Ferrari, V., Tuytelaars, T., Van Gool, L.: Simultaneous object recognition and segmentation by image exploration. In: Proceedings of the 8th European Conference on Computer Vision, Prague, Czech Republic, pp. 40–54 (2004)
Moreels, P., Perona, P.: A probabilistic cascade of detectors for individual object recognition. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 426–439. Springer, Heidelberg (2008)
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Kouskouridas, R., Gasteratos, A. (2010). Visual Assistance to an Advanced Mechatronic Platform for Pick and Place Tasks. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16587-0_64
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DOI: https://doi.org/10.1007/978-3-642-16587-0_64
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