Open Access
| Issue |
MATEC Web Conf.
Volume 244, 2018
Innovative Technologies in Engineering Production (ITEP’18)
|
|
|---|---|---|
| Article Number | 01027 | |
| Number of page(s) | 7 | |
| Section | Progressives Technologies | |
| DOI | https://doi.org/10.1051/matecconf/201824401027 | |
| Published online | 05 December 2018 | |
- J. Brethé, D.Lefebvre, Risk ellipsoids and granularity ration for industrial robot. International Journal of Factory Automation Robotics and Soft computing, 2, 93-101 (2007) [Google Scholar]
- I. Kuric, V. Bulej, M. Sága, P. Pokorný, Development of simulation software for mobile robot path planning within multilayer map system based on metric and topological maps. International journal of advanced robotic systems, 14, (2017) [Google Scholar]
- B. Mičieta, M. Edl, M. Krajčovič, Ľ. Dulina, P. Bubeník, L. Ďurica, V. Biňasová, Delegate MASs for Coordination and Control of One-Directional AGV Systems: A Proof-of-Concept. International journal of advanced manufactur. technology, 94, 415-431 (2018) [Google Scholar]
- W. S. Newman, C. E. Birkhimer, R. J. Horning, A. T. Wilkey, Calibration of a Motoman P8 robot based on laser tracking. Robotics and Automation, 2000. Proceedings. ICRA’00. IEEE International Conference on. 4, 3597-3602 (2000) [CrossRef] [Google Scholar]
- M. Císar, I. Zajačko, I. Kuric, Diagnostics based on poositioning performance during circular motion. Inżynier XXI wieku: projektujemy przyszłość. 536-542 (2016) [Google Scholar]
- A. Sapietová, M. Sága, I. Kuric, Š. Václav, Application of optimization algorithms for robot systems designing. International Journal of Advanced Robotic Systems, 15 (2018) [Google Scholar]
- V. Tlach, M. Císar, I. Kuric, Zajačko, Determination of the Industrial Robot Positioning Performance. MATEC Web of Conferences. 137 (EDP Sciences, 2017) [Google Scholar]
- A. Nubiola, I. A. Bonev, Absolute calibration of an ABB IRB 1600 robot using a laser tracker. Robotics and Computer-Integrated Manufacturing, 29, 236-245 (2013) [CrossRef] [Google Scholar]
- M. Abderrahim, A. Khamis, S. Garrido, L. Moreno, Accuracy and Calibration Issues of Industrial Manipulators. Industrial Robotics-Programming, Simulation and Applications, 131-146 (2007) [Google Scholar]
- J. Józwik, D. Ostrowski, P. Jarosz, D. Mika, Industrial robot repeatability testing with high speed camera Phantom v2511. Advances in Science and Technology Research Journal, 10, 86-96 (2016) [CrossRef] [Google Scholar]
- D. Kumičakova, V. Tlach, M. Cisar. Testing the performance characteristics of manipulating industrial robots. Transactions of the VŠB - Technical University of Ostrava: mechanical series, 62, 39-50 (2016) [Google Scholar]
- A. Şirinterlikçi, M. Tiryakioǧlu, A. Bird, A. Harris, K. Kweder, Repeatability and Accuracy of an Industrial Robot: Laboratory Experience for a Design of Experiments Course. Technology Interface Journal, 9 (2009) [Google Scholar]
- Charu C Aggarwal, Neural Networks and Deep Learning. Springer, 2018 [CrossRef] [Google Scholar]
- Ragav V., Baoxin L., Convolutional Neural Networks in Visual Computing. CRC Press, 2017 [Google Scholar]
- A. Nubiola, M. Slamani, I. A. Bonev, A new method for measuring a large set of poses with a single telescoping ballbar. Precision Engineering, 37, 451-460 (2013) [CrossRef] [Google Scholar]
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