Parallelized Flight Path Prediction using a Graphics Processing Unit
Maximilian Götzinger, Martin Pongratz, Amir M. Rahmani, Axel Jantsch
2017
Abstract
Summarized under the term Transport-by-Throwing, robotic arms throwing objects to each other are a visionary system intended to complement the conventional, static conveyor belt. Despite much research and many novel approaches, no fully satisfactory solution to catch a ball with a robotic arm has been developed so far. A new approach based on memorized trajectories is currently being researched. This paper presents an algorithm for real-time image processing and flight prediction. Object detection and flight path prediction can be done fast enough for visual input data with a frame rate of 130 FPS (frames per second). Our experiments show that the average execution time for all necessary calculations on an NVidia GTX 560 TI platform is less than 7.7ms. The maximum times of up to 11.7ms require a small buffer for frame rates over 85 FPS. The results demonstrate that the use of a GPU (Graphics Processing Unit) considerably accelerates the entire procedure and can lead to execution rates of 3.5 to 7.2 faster than on a CPU. Prediction, which was the main focus of this research, is accelerated by a factor of 9.5 by executing the devised parallel algorithm on a GPU. Based on these results, further research could be carried out to examine the prediction system’s reliability and limitations (compare (Pongratz, 2016)).
References
- Askari, M. et al. (2013). Parallel gpu implementation of hough transform for circles. In IJCSI.
- Barteit, D. et al. (2009). Measuring the intersection of a thrown object with a vertical plane. In INDIN.
- Bäuml, B. et al. (2011). Catching flying balls and preparing coffee: Humanoid rollin'justin performs dynamic and sensitive tasks. In ICRA.
- Chen, S. et al. (2011). Accelerating the hough transform with cuda on graphics processing units. Department of Computer Science, Arkansas State University.
- D'Orazio, T. et al. (2002). A ball detection algorithm for real soccer image sequences. In ICPR.
- Fung, J. et al. (2005). Openvidia: Parallel gpu computer vision. In ACM Multimedia.
- Gowanlock, M. et al. (2015). Indexing of spatiotemporal trajectories for efficient distance threshold similarity searches on the gpu. In IPDPS.
- Hong, W. et al. (1995). Experiments in hand-eye coordination using active vision. In Lecture Notes in Control and Information Sciences.
- Jacobs, L. et al. (2013). Object tracking in noisy radar data: Comparison of hough transform and ransac. In EIT.
- Karimi, K. et al. (2010). A performance comparison of CUDA and opencl. CoRR, abs/1005.2581.
- Khronos, G. (2015). Opencl.
- Luo, Y. et al. (2008). Canny edge detection on nvidia cuda. In CVPRW.
- NVidia, C. (2014). Cuda architecture.
- NVidia, C. (2015). Geforce gtx 560 ti.
- Ogawa, K. et al. (2010). Efficient canny edge detection using a gpu. In ICNC.
- Pongratz, M. (2009). Object touchdown position prediction. Master's thesis, Vienna University of Technology.
- Pongratz, M. (2016). Bio-inspired transport by throwing system; an analysis of analytical and bio-inspired approaches. PhD thesis, TU Wien 2016.
- Pongratz, M. et al. (2010). Transport by throwing - a bioinspired approach. In INDIN.
- Pongratz, M. et al. (2012). Koros initiative: Automatized throwing and catching for material transportation. In Leveraging Applications of Formal Methods, Verification, and Validation, pages 136-143.
- Tang, X. et al. (2015). Efficient selection algorithm for fast k-nn search on gpus. In IPDPS.
- Wang, W. et al. (2011). Robust spatial matching for object retrieval and its parallel implementation on gpu. IEEE Transactions on Multimedia, 13(6).
- Wu, S. et al. (2012). Parallelization research of circle detection based on hough transform. In IJCSI.
Paper Citation
in Harvard Style
Götzinger M., Pongratz M., Rahmani A. and Jantsch A. (2017). Parallelized Flight Path Prediction using a Graphics Processing Unit . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 386-393. DOI: 10.5220/0006105903860393
in Bibtex Style
@conference{visapp17,
author={Maximilian Götzinger and Martin Pongratz and Amir M. Rahmani and Axel Jantsch},
title={Parallelized Flight Path Prediction using a Graphics Processing Unit},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={386-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006105903860393},
isbn={978-989-758-227-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - Parallelized Flight Path Prediction using a Graphics Processing Unit
SN - 978-989-758-227-1
AU - Götzinger M.
AU - Pongratz M.
AU - Rahmani A.
AU - Jantsch A.
PY - 2017
SP - 386
EP - 393
DO - 10.5220/0006105903860393