Abstract
The detection and pose estimation of various shaped objects in real world cluttered application scenarios is a major technical challenge due to noisy sensor data and possible occlusions. Usually, a predefined model database is utilized for implementing a robust and reliable object detection system. Geometric models based on superquadrics have shown great potential and flexibility for representing a variety of shapes by using only a few parameters. In this paper, we propose a novel method concerning superquadric based Segment-then-fit approach and evaluate it in a logistic application scenario. The method utilizes boundary and region information to recover different types of convex shaped logistic goods in cluttered scenarios for automated handling by means of unorganized point cloud data. We have evaluated our approach using synthetic and multiple real sensor data on several packaging scenarios with various shaped logistic goods.
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References
Scholz-Reiter, B., Echelmeyer, W., Wellbrock, E.: Development of a robot-based system for automated unloading of variable packages out of transport units and containers. In: IEEE International Conference on Automation and Logistics, pp. 2766–2770 (2008)
Echelmeyer, W., Kirchheim, A., Lilienthal, A.J., Akbiyik, H., Bonini, M.: Performance indicators for robotics systems in logistics applications. In: IEEE/RSJ IROS Workshop on Metrics and Methodologies for Autonomous Robot Teams in Logistics (2011)
Biegelbauer, G., Vincze, M., Wohlkinger, W.: Model-based 3d object detection. Machine Vision and Applications 21, 497–516 (2010)
Barr, A.H.: Superquadrics and angle-preserving transformations. IEEE Comput. Graph. Appl. 1(1), 11–23 (1981)
Solina, F., Bajcsy, R.: Recovery of parametric models from range images: The case for superquadrics with global deformations. IEEE Trans. Pattern Anal. Mach. Intell. 12(2), 131–147 (1990)
Katsoulas, D., Bastidas, C.C., Kosmopoulos, D.: Superquadric segmentation in range images via fusion of region and boundary information. IEEE Trans. Pattern Anal. Mach. Intell. 30(5), 781–795 (2008)
Strand, M., Dillmann, R.: Segmentation and approximation of objects in pointclouds using superquadrics. In: International Conference on Information and Automation, pp. 887–892 (2009)
Gupta, A., Bajcsy, R.: Volumetric segmentation of range images of 3d objects using superquadric models. Computer Vision Graphics and Image Processing: Image Understanding 58(3), 302–326 (1993)
Jaklič, A., Leonardis, A., Solina, F.: Segmentation and Recovery of Superquadrics. Computational imaging and vision, vol. 20. Kluwer, Dordrecth (2000) ISBN 0-7923-6601-8
Rusu, R.B.: Semantic 3d object maps for everyday manipulation in human living environments, pp. 46–50, 88–90. Springer (2010)
Rusu, R., Cousins, S.: 3d is here: Point cloud library (pcl). In: IEEE International Conference on Robotics and Automation, pp. 1–4 (2011)
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Thamer, H., Taj, F., Weimer, D., Kost, H., Scholz-Reiter, B. (2013). Combined Categorization and Localization of Logistic Goods Using Superquadrics. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_25
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DOI: https://doi.org/10.1007/978-3-642-39094-4_25
Publisher Name: Springer, Berlin, Heidelberg
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