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M. Götzinger, M. Pongratz, A. Rahmani, A. Jantsch:
"Parallelized Flight Path Prediction Using a Graphics Processing Unit";
Poster: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. (VISAPP17), Porto, Portugal; 27.02.2017 - 01.03.2017; in: "Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. (VISAPP17)", (2017), 8 S.

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 than7.7ms. 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)).

CUDA, GPU, Canny, RANSAC, Image Processing, Parallel Algorithm, Flight Path Prediction, Based on Memorized Trajectories