Agung Julius

Agung Julius

Professor, Mechanical, Aerospace, and Nuclear Engineering

Research Expertise
Control systems, robotics, optimization
Research

Applications of control theory, optimization, and machine learning on industry relevant problems, e.g., robotics.

Publications

Y. Wen, H. He, A. A. Julius, J. T. Wen, Motion Profile Optimization in Industrial Robots using Reinforcement Learning, Proc. IEEE/ASME Int. Conf. Advanced Intelligent Mechatronics (AIM 2023), 2023.

H. He, C-l. Lu, Y. Wen, G. Saunders, P. Yang, J. Schoonover, J. Wason, A. A. Julius, J.T. Wen, High-Speed High-Accuracy Spatial Curve Tracking Using Motion Primitives in Industrial Robots, Proc. IEEE International Conference on Robotics and Automation (ICRA 2023), pp. 12289-12295, 2023.

R. Yan, T. Ma, A. Fokoue, M. Chang, and A. A. Julius, Neuro-symbolic Models for Interpretable Time Series Classification using Temporal Logic Description, Proc. IEEE International Conference on Data Mining, 2022.

N. Baharisangari, K. Hirota, R. Yan, A. A. Julius and Z. Xu, Weighted Graph-Based Signal Temporal Logic Inference Using Neural Networks, IEEE Control Systems Letters, Vol. 6, pp. 2096-2101, 2021.

Z. Xu, A.A. Julius, J. H. Chow, Energy Storage Controller Synthesis for Power Systems with Temporal Logic Specifications, IEEE Systems Journal, vol. 13(1), pp. 748-759, 2019.

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