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Department of Electrical and Computer Engineering

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Zhou, S., Helwa, M. K., Schoellig, A. P., Sarabakha, A. & Kayacan, E. (2019). Knowledge transfer between robots with similar dynamics for high-accuracy impromptu trajectory tracking. In 2019 18th European Control Conference, ECC 2019 Article 8796140 IEEE. https://doi.org/10.23919/ECC.2019.8796140

Zhang, C., Rossi, C. & Kayacan, E. (2017). Interval Type-2 Fuzzy-Neuro Control of Nonlinear Systems With Proved Overall System Stability. In 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017 (pp. 1-6). Article 8015495 IEEE. https://doi.org/10.1109/FUZZ-IEEE.2017.8015495

Yan, R.-J., Wu, J., Yeung Lee, J., Manan Khan, A., Han, C.-S., Kayacan, E. & Chen, I.-M. (2016). A Novel Method for 3D Reconstruction: Division and Merging of Overlapping B-spline surfaces. Computer-Aided Design, 81, 14-23. https://doi.org/10.1016/j.cad.2016.08.007

Yan, R.-J., Kayacan, E., Chen, I.-M. & Kong Tiong, L. (2017). A novel building post-construction quality assessment robot: Design and prototyping. In IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 6020-6026). Article 8206499 IEEE. https://doi.org/10.1109/IROS.2017.8206499

Yan, R.-J., Leong Low, C., Duan, J., Liu, L., Kayacan, E., Chen, I.-M. & Tiong, R. (2017). Development of a Novel Post-Construction Quality Assessment Robot System. In 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 (pp. 1-6). Article 7838741 IEEE . https://doi.org/10.1109/ICARCV.2016.7838741

Yan, R. J., Kayacan, E., Chen, I. M., Tiong, L. K. & Wu, J. (2019). QuicaBot: Quality Inspection and Assessment Robot. IEEE Transactions on Automation Science and Engineering, 16(2), 506-517. https://doi.org/10.1109/TASE.2018.2829927

Wilson Lee, Y. J., Mehndiratta, M. & Kayacan, E. (2018). Fly without borders with Additive Manufacturing: A microscale tilt-rotor Tricopter Design. In Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (Vol. 2018-May, pp. 256-261) https://doi.org/10.25341/D43K5G

V. Topalev, A., Oniz, Y., Kayacan, E. & Kaynak, O. (2011). Neuro-Fuzzy Control of Antilock Braking System Using Sliding Mode Incremental Learning Algorithm. Neurocomputing, 74(11), 1883-1893. https://doi.org/10.1016/j.neucom.2010.07.035

V. Topalev, A., G. Shakev, N., Kaynak, O. & Kayacan, E. (2010). Neuro-adaptive Approach for Controlling a Quad-rotor Helicopter Using Sliding Mode Learning Algorithm. In IFAC Proceedings Volumes (10 ed., Vol. 43, pp. 94-99). Elsevier. https://doi.org/10.3182/20100826-3-TR-4015.00020

V. Topalev, A., Kayacan, E., Oniz, Y. & Kaynak, O. (2009). Neuro-Fuzzy Control of Antilock Braking System Using Variable-Structure-Systems-based Learning Algorithm. In Adaptive and Intelligent Systems, 2009. ICAIS '09. International Conference on (pp. 166-171). IEEE . https://doi.org/10.1109/ICAIS.2009.35

V. Topalev, A., Kayacan, E., Oniz, Y. & Kaynak, O. (2009). Adaptive Neuro-Fuzzy Control with Sliding Mode Learning Algorithm: Application to Antilock Braking System. In Asian Control Conference, 2009. ASCC 2009. 7th (pp. 784-789). IEEE . https://ieeexplore.ieee.org/document/5276234/

Van Beers, R., Gutierrez, L. L., Schenk, A., Nicolai, B., Kayacan, E. & Saeys, W. (2014). Optical measurement techniques for the ripeness determination of Braeburn apples. In Proceedings International Conference of Agricultural Engineering (pp. 1-7) http://www.geyseco.es/geystiona/adjs/comunicaciones/304/C02000001.pdf

Ugurlu, H. I., Pham, X. H. & Kayacan, E. (2022). Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots. Robotics, 11(5), Article 109. https://doi.org/10.3390/robotics11050109

Thanh Nguyen, T., Vandevoorde, K., Wouters, N., Kayacan, E., G. de Baerdemaeker, J. & Saeys, W. (2016). Detection of red and bicoloured apples on tree with an RGB-D camera. Biosystems Engineering, 146, 33-44. https://doi.org/10.1016/j.biosystemseng.2016.01.007

Thanh Nguyen, T., Kayacan, E., G. de Baerdemaeker, J. & Saeys, W. (2013). Task and Motion Planning for Apple-Harvesting Robot. In IFAC Proceedings Volumes (18 ed., Vol. 46, pp. 247-252). Elsevier. https://doi.org/10.3182/20130828-2-SF-3019.00063

Thanh Nguyen, T., Keresztes, J., Vandevoorde, K., Kayacan, E., G. de Baerdemaeker, J. & Saeys, W. (2014). Apple detection algorithm for robotic harvesting using a RGB-D camera. In Proceedings International Conference of Agricultural Engineering (pp. 1-8) https://pdfs.semanticscholar.org/d294/58c25c8bde8492c15eacb96c871c2030f2c5.pdf

Sarabakha, A., Fu, C., Kayacan, E. & Kumbasar, T. (2016). Type-2 Fuzzy Logic Controllers Made Even Simpler: From Design to Deployment in Real-Time for Quadcopter UAVs. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=Hz3f8N-30dg

Sarabakha, A., Fu, C., Kayacan, E. & Kumbasar, T. (2018). Type-2 Fuzzy Logic Controllers Made Even Simpler: From Design to Deployment in Real-Time for Quadcopter UAVs. IEEE Transactions on Industrial Electronics, 65(6), 5069-5077. https://doi.org/10.1109/TIE.2017.2767546

Sarabakha, A., Imanberdiyev, N., Kayacan, E., Ahmadieh Khanesar, M. & Hagras, H. (2017). Novel Levenberg-Marquardt Based Learning Algorithm for Unmanned Aerial Vehicles. Information Sciences, 417, 361-380. https://doi.org/10.1016/j.ins.2017.07.020

Sarabakha, A., Fu, C. & Kayacan, E. (2017). Double-Input Interval Type-2 Fuzzy Logic Controllers: Analysis and Design. In 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017 (pp. 1-6). Article 8015485 IEEE . https://doi.org/10.1109/FUZZ-IEEE.2017.8015485

Sarabakha, A. & Kayacan, E. (2016). Y6 tricopter autonomous evacuation in an Indoor Environment using Q-learning algorithm. In 2016 IEEE 55th Conference on Decision and Control, CDC 2016 (pp. 5992-5997). Article 7799189 IEEE . https://doi.org/10.1109/CDC.2016.7799189

Sarabakha, A., Fu, C. & Kayacan, E. (2019). Intuit before tuning: Type-1 and type-2 fuzzy logic controllers. Applied Soft Computing Journal, 81, Article 105495. https://doi.org/10.1016/j.asoc.2019.105495

Sarabakha, A. & Kayacan, E. (2019). Online deep learning for improved trajectory tracking of unmanned aerial vehicles using expert knowledge. In 2019 International Conference on Robotics and Automation, ICRA 2019 (pp. 7727-7733). Article 8794314 IEEE. https://doi.org/10.1109/ICRA.2019.8794314

Sarabakha, A. & Kayacan, E. (2020). Online Deep Fuzzy Learning for Control of Nonlinear Systems Using Expert Knowledge. IEEE Transactions on Fuzzy Systems, 28(7), 1492-1503. https://doi.org/10.1109/TFUZZ.2019.2936787

Rubio Hervas, J., Reyhanoglu, M., Tang, H. & Kayacan, E. (2015). Nonlinear control of fixed-wing UAVs in presence of stochastic winds. Communications in Nonlinear Science and Numerical Simulation, 33, 57-69. https://doi.org/10.1016/j.cnsns.2015.08.026

Rubio Hervas, J., Kayacan, E., Reyhanoglu, M. & Tang, H. (2014). Sliding Mode Control of Fixed- Wing UAVs in Windy Environments. In Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on (pp. 986-991). IEEE . https://doi.org/10.1109/ICARCV.2014.7064440

Ravindrababu, S., Govdeli, Y., Wei Wong, Z. & Kayacan, E. (2018). Evaluation of the Influence of Build and Print Orientations of Unmanned Aerial Vehicle Parts Fabricated Using Fused Deposition Modeling Process. Journal of Manufacturing Processes, 34(Part A), 659-666. https://doi.org/10.1016/j.jmapro.2018.07.007

Qiao, Z., Pham, X. H., Ramasamy, S., Jiang, X., Kayacan, E. & Sarabakha, A. (2024). Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing. In IJCNN 2024 Conference Proceedings IEEE. https://doi.org/10.1109/ijcnn60899.2024.10649903

Prach, A. & Kayacan, E. (2018). An MPC-based Position Controller for a Tilt-Rotor Tricopter VTOL UAV. Optimal Control, Applications and Methods, 39(1), 343-356. https://doi.org/10.1002/oca.2350

Prach, A., Kayacan, E. & S. Bernstein, D. (2016). An Experimental Evaluation of the Forward Propagating Riccati Equation to Nonlinear Control of the Quanser 3 DOF Hover Testbed. In 2016 American Control Conference, ACC 2016 (pp. 3710-3715). Article 7525490 IEEE. https://doi.org/10.1109/ACC.2016.7525490

Pham, X. H., Bozcan, I., Sarabakha, A., Haddadin, S. & Kayacan, E. (2021). GateNet: An Efficient Deep Neural Network Architecture for Gate Perception Using Fish-Eye Camera in Autonomous Drone Racing. Paper presented at 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, Prag, Czech Republic. https://sarabakha.info/files/papers/conference/IROS_2021.pdf

Pham, H. X., Ugurlu, H. I., Fevre, J. L., Bardakci, D. & Kayacan, E. (2022). Deep learning for vision-based navigation in autonomous drone racing. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 371-406). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00020-8

Pham, X. H., Sarabakha, A., Odnoshyvkin, M. & Kayacan, E. (2022). PencilNet: Zero-Shot Sim-to-Real Transfer Learning for Robust Gate Perception in Autonomous Drone Racing. IEEE Robotics and Automation Letters, 7(4), 11847 - 11854. https://doi.org/10.1109/LRA.2022.3207545

Pham, X. H., Heiß, M., Tran, D., Nguyen, M. A., Nguyen, A. Q. & Kayacan, E. (2023). ORB-Net: End-to-end Planning Using Feature-based Imitation Learning for Autonomous Drone Racing. In ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (pp. 16-21). VDE Verlag GmbH. https://ieeexplore.ieee.org/document/10363048

Patel, S., Sarabakha, A., Kircali, D. & Kayacan, E. (2020). An Intelligent Hybrid Artificial Neural Network-Based Approach for Control of Aerial Robots. Journal of Intelligent and Robotic Systems: Theory and Applications, 97(2), 387-398. https://doi.org/10.1007/s10846-019-01031-z

Oniz, Y., Kayacan, E. & Kaynak, O. (2008). A Dynamic Method to Forecast the Wheel Slip for Antilock Braking System and Its Experimental Evaluation. IEEE Transactions on Cybernetics, 39(2), 551-560. https://doi.org/10.1109/TSMCB.2008.2007966

Oniz, Y., Kayacan, E., Cisel Aras, A., Kaynak, O. & H. Abiyev, R. (2010). A servo system control with time-varying load using type-2 fuzzy neural system, In IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society (pp. 35-40). IEEE. https://doi.org/10.1109/IECON.2010.5675372

Oniz, Y., Kayacan, E. & Kaynak, O. (2008). Simulated and Experimental Study of Antilock Braking System Using Grey Sliding Mode Control. In Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on (pp. 90-95). IEEE . https://doi.org/10.1109/ICSMC.2007.4413975

Oniz, Y., Kayacan, E. & Kaynak, O. (2007). A Grey Sliding Mode Controller Design for Antilock Braking System. In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (pp. 1-8). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2007-34563

Oniz, Y., Kayacan, E. & Kaynak, O. (2007). Kilitlenmeyen Fren Sistemi (KFS) icin Gri Kayma Kipli Denetleyici Tasarimi. In TOK 2007 - Otomatik Kontrol Ulusal Toplantisi (pp. 506-511)

Ong, Z. Q. G., Govdeli, Y., Ravindrababu, S. & Kayacan, E. (2018). Feasibility Studies of Postprocessing Techniques to Strenghten 3D Printed UAV Wing Structures. In Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (Vol. 2018-May, pp. 244-249) https://doi.org/10.25341/D4WW2K

Morales, T., Sarabakha, A. & Kayacan, E. (2020). Image Generation for Efficient Neural Network Training in Autonomous Drone Racing. In 2020 International Joint Conference on Neural Networks (IJCNN) Article 9206943 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206943

Mehndiratta, M., Kayacan, E., Patel, S., Kayacan, E. & Chowdhary, G. (2019). Learning-based Fast Nonlinear Model Predictive Control for Custom-made 3D Printed Ground and Aerial Robots. In S. V. Rakovic & W. Levine (Eds.), Handbook of Model Predictive Control (1 ed., pp. 581-605). Birkhäuser Verlag. https://doi.org/10.1007/978-3-319-77489-3_24

Mehndiratta, M. & Kayacan, E. (2016). Numerical Investigation of Gaussian Filters with a Combined Type Bayesian Filter for Nonlinear State Estimation. In IFAC-PapersOnLine (18 ed., Vol. 49, pp. 446-453). Elsevier. https://doi.org/10.1016/j.ifacol.2016.10.206

Mehndiratta, M., Kayacan, E. & Kumbasar, T. (2016). Design and Experimental Validation of Single Input Type-2 Fuzzy PID Controllers as Applied to 3 DOF Helicopter Testbed. In 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 (pp. 1584-1591). Article 07737879 IEEE. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7737879

Mehndiratta, M. & Kayacan, E. (2018). Reconfigurable Fault-tolerant NMPC for Y6 Coaxial Tricopter with Complete Loss of One Rotor. In 2018 IEEE Conference on Control Technology and Applications, CCTA 2018: CCTA (pp. 774-780). Article 8511444 IEEE. https://doi.org/10.1109/CCTA.2018.8511444

Mehndiratta, M., Kayacan, E. & Kayacan, E. (2018). A Simple Learning Strategy for Feedback Linearization Control of Aerial Package Delivery Robot. In 2018 IEEE Conference on Control Technology and Applications, CCTA 2018: CCTA (pp. 361-367). Article 8511485 IEEE. https://doi.org/10.1109/CCTA.2018.8511485

Mehndiratta, M. & Kayacan, E. (2018). Online Learning-based Receding Horizon Control of Tilt-rotor Tricopter: A Cascade Implementation. In 2018 Annual American Control Conference, ACC 2018 (pp. 6378-6383). Article 8430814 IEEE. https://doi.org/10.23919/ACC.2018.8430814

Mehndiratta, M., Camci, E. & Kayacan, E. (2018). Automated Tuning of Nonlinear Model Predictive Controller by Reinforcement Learning. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018: IROS (pp. 3016-3021). Article 8594350 IEEE. https://doi.org/10.1109/IROS.2018.8594350

Mehndiratta, M. & Kayacan, E. (2019). A constrained instantaneous learning approach for aerial package delivery robots: onboard implementation and experimental results. Autonomous Robots, 43(8), 2209-2228. https://doi.org/10.1007/s10514-019-09875-y

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Revised 10.08.2023

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Andriy Sarabakha