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Akos Csiszar
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2020 – today
- 2021
- [c20]Akos Csiszar, Viktor Krimstein, Justus Bogner
, Alexander Verl:
Generating Reinforcement Learning Environments for Industrial Communication Protocols. AI4I 2021: 57-60 - 2020
- [c19]Ralf Gulde, Marc Tuscher, Akos Csiszar, Oliver Riedel
Deep Reinforcement Learning using Cyclical Learning Rates. AI4I 2020: 32-35 - [c18]Akos Csiszar, Philipp Hein
Towards a user-centered development process of machine learning applications for manufacturing domain experts. AI4I 2020: 36-39 - [c17]Johannes R. Walter, Harnoor Saini, Benjamin Maier, Naser Mostashiri
Comparative Study of a Biomechanical Model-based and Black-box Approach for Subject-Specific Movement Prediction*. EMBC 2020: 4775-4778 - [i2]Ralf Gulde, Marc Tuscher, Akos Csiszar, Oliver Riedel, Alexander Verl:
Reinforcement Learning Approach to Vibration Compensation for Dynamic Feed Drive Systems. CoRR abs/2004.09263 (2020) - [i1]Ralf Gulde, Marc Tuscher, Akos Csiszar, Oliver Riedel, Alexander Verl:
Deep Reinforcement Learning using Cyclical Learning Rates. CoRR abs/2008.01171 (2020)
2010 – 2019
- 2019
- [c16]Ralf Gulde, Marc Tuscher, Akos Csiszar, Oliver Riedel
Reinforcement Learning Approach to Vibration Compensation for Dynamic Feed Drive Systems. AI4I 2019: 26-29 - [c15]Florian Jaensch, Akos Csiszar, Janik Sarbandi, Alexander Verl:
Reinforcement Learning of a Robot Cell Control Logic using a Software-in-the-Loop Simulation as Environment. AI4I 2019: 79-84 - [c14]Raphael Kusumoto, Luigi Palmieri
Informed Information Theoretic Model Predictive Control. ICRA 2019: 2047-2053 - 2018
- [j1]Christian Friedrich
Efficient Task and Path Planning for Maintenance Automation Using a Robot System. IEEE Trans Autom. Sci. Eng. 15(3): 1205-1215 (2018) - [c13]Florian Jaensch, Akos Csiszar, Annika Kienzlen, Alexander Verl:
Reinforcement Learning of Material Flow Control Logic Using Hardware-in-the-Loop Simulation. AI4I 2018: 77-80 - [c12]Florian Jaensch, Akos Csiszar, Christian Scheifele, Alexander Verl:
Digital Twins of Manufacturing Systems as a Base for Machine Learning. M2VIP 2018: 1-6 - [c11]Benjamin Kaiser, Akos Csiszar, Alexander Verl:
Generative models for direct generation of CNC toolpaths. M2VIP 2018: 1-6 - 2017
- [c10]Christian Friedrich, Akos Csiszar, Armin Lechler, Alexander Verl:
Fast robot task and path planning based on CAD and vision data. AIM 2017: 1633-1638 - [c9]Akos Csiszar, Jan Eilers, Alexander Verl:
On solving the inverse kinematics problem using neural networks. M2VIP 2017: 1-6 - 2016
- [c8]Akos Csiszar:
A combinatorial approach to the automated generation of inverse kinematics equations for robot arms. CASE 2016: 984-989 - [c7]Caren Dripke, Sara Höhr, Akos Csiszar, Alexander Verl:
A Concept for the Application of Reinforcement Learning in the Optimization of CAM-Generated Tool Paths. ML4CPS 2016: 1-8 - 2015
- [c6]Akos Csiszar:
A combinatorial optimization approach to the Denavit-Hartenberg parameter assignment. AIM 2015: 1451-1456 - [c5]Akos Csiszar, Philipp Sommer, Armin Lechler:
EcoBotics: Advantages and challenges of building a bamboo robot arm. ICIT 2015: 192-197 - [c4]Martin Mikusz, Akos Csiszar:
CPS Platform Approach to Industrial Robots: State of the Practice, Potentials, Future Research Directions. PACIS 2015: 176 - 2014
- [c3]Agus Atmosudiro, Matthias Keinert, Ali Karim, Armin Lechler, Alexander Verl, Akos Csizar:
Productivity Increase through Joint Space Path Planning for Robot Machining. EMS 2014: 257-262 - 2013
- [c2]Razvan-Vlad Vasiu, Calin Rusu
Conceptual development of a reconfigurable parallel robot. AIM 2013: 1193-1198
2000 – 2009
- 2008
- [c1]R. Pacurari, M. Crenganis, Akos Csiszar, Cornel Brisan:
Possibilities Concerning Control of a Laser Welding Cell Utilizing Servomotors and PLC. EIAT/IETA 2008: 303-308
Coauthor Index
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