@inproceedings{BeckeSchlegl, author = {Becke, Mark and Schlegl, Thomas}, title = {Least squares pose estimation of cylinder axes from multiple views using contour line features}, series = {IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, 9-12 Nov. 2015, Yokohama, Japan}, booktitle = {IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, 9-12 Nov. 2015, Yokohama, Japan}, publisher = {IEEE}, doi = {10.1109/IECON.2015.7392371}, pages = {1855 -- 1861}, abstract = {In this paper, a new method for a minimum-error pose estimation of cylinder axes based on apparent contour line features from multiple views is presented. Novel model equations for both single and particularly multiple views are derived, and based upon these, an iterative algorithm for least squares fitting the model to imaged cylinder contour line features is introduced. The good performance and fast convergence of the proposed algorithm is shown by solving exemplary fitting problems.}, language = {en} } @inproceedings{Becke, author = {Becke, Mark}, title = {On Modeling and Least Squares Fitting of Cylinders from Single and Multiple Views Using Contour Line Features}, series = {Intelligent Robotics and Applications}, volume = {9246}, booktitle = {Intelligent Robotics and Applications}, editor = {Liu, Honghai and Kubota, Naoyuki and Zhu, Xiangyang and Dillmann, R{\"u}diger}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-22872-3}, doi = {10.1007/978-3-319-22873-0_33}, pages = {372 -- 385}, abstract = {In this paper, a new method for a minimum-error pose estimation of cylinder axes based on apparent contour line features from multiple views is presented. Novel model equations for both single and particularly multiple views are derived, and based upon these, an algorithm for least squares fitting the model to imaged cylinder contour line features is introduced. The good performance of the proposed algorithm is shown by solving an exemplary fitting problem.}, language = {en} } @inproceedings{LangBeckeSchlegl, author = {Lang, Jonas and Becke, Mark and Schlegl, Thomas}, title = {A Systematic Approach for the Parameterisation of the Kernel-Based Hough Transform Using a Human-Generated Ground Truth}, series = {Intelligent Robotics and Applications}, volume = {9244}, booktitle = {Intelligent Robotics and Applications}, editor = {Liu, Honghai and Kubota, Naoyuki and Zhu, Xiangyang and Dillmann, R{\"u}diger and Zhou, Dalin}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-22878-5}, doi = {10.1007/978-3-319-22879-2_44}, pages = {473 -- 486}, abstract = {Lines are one of the basic features that are used to characterise the content of an image and to detect objects. Unlike edges or segmented blobs, lines are not only an accumulation of certain feature pixels but can also be described in an easy and exact mathematical way. Besides a lot of different detection methods, the Hough transform has gained much attention in recent years. With increasing processing power and continuous development, computer vision algorithms get more powerful with respect to speed, robustness and accuracy. But there still arise problems when searching for the best parameters for an algorithm or when characterising and evaluating the results of feature detection tasks. It is often difficult to estimate the accuracy of an algorithm and the influences of the parameter selection. Highly interdependent parameters and preprocessing steps continually lead to only hardly comprehensible results. Therefore, instead of pure trial and error and subjective ratings, a systematic assessment with a hard, numerical evaluation criterion is suggested. The paper at hand deals with the latter ones by using a human-generated ground truth to approach the problem. Thereby, the accuracy of the surveyed Kernel-based Hough transform algorithm was improved by a factor of three. These results are used for the tracking of cylindrical markers and to reconstruct their spatial arrangement for a biomedical research application.}, language = {en} } @inproceedings{KotzStapfBecke, author = {Kotz, Oliver and Stapf, Matthias and Becke, Mark}, title = {GPU-Based Task Specific Evaluation of the Dynamic Performance of a 6DOF Manipulator}, series = {Intelligent Robotics and Applications. 8th International Conference, ICIRA 2015, Portsmouth, UK, August 24-27, 2015, Proceedings, Part II}, booktitle = {Intelligent Robotics and Applications. 8th International Conference, ICIRA 2015, Portsmouth, UK, August 24-27, 2015, Proceedings, Part II}, publisher = {Springer}, address = {Cham}, doi = {10.1007/978-3-319-22876-1_30}, pages = {345 -- 357}, abstract = {This paper addresses the problem of properly placing a given task in the manipulator workspace by a heuristic and numeric approach. Thus, the task is placed relatively to the manipulator for each element of the discretized workspace and the required joint torques are determined. The results are are by a torque-based optimization criterion. The modularity of this approach ensures general applicability on various systems and tasks while the high computational effort is treated by GPU parallelization. The method is presented for a given 6DOF manipulator and a highly dynamic trajectory. The resulting interactive map of the manipulator workspace gives an overview of the task dependent dynamic performance, detailed evaluation of certain solutions will show the dexterity of the proposed approach.}, language = {en} }