Projects per year
Personal profile
Personal profile
Dr Matteo Rubagotti obtained his PhD in Electronics, Computer Science and Electrical Engineering (track in Automatic Control) at the University of Pavia, Pavia, Italy, in 2010. Previously to his post at Nazarbayev University, he was lecturer at the University of Leicester, Leicester, UK, and postdoctoral fellow at the University of Trento, Trento, Italy, and at IMT Institute for Advanced Studies, Lucca, Italy. He also spent visiting periods at the Center for Automotive Research of The Ohio State University, OH, USA, and at the Automatic Control Lab, ETH Zurich, Zurich Switzerland.
Research interests
His research interests include model predictive control, sliding mode control, and the application of control and optimization algorithms to solve research problems in robotics (variable-impedance-actuated robots, parallel manipulators, tensegrity robots, and physical human-robot interaction).
Teaching
At Nazarbayev University, Dr Rubagotti has been teaching a number of courses at undergraduate and graduate level in the fields of signal processing, system dynamics, control theory, and robot motion planning.
External positions
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Development of Shared Autonomy Human–Machine Control Interfaces for Intelligent Wheelchair Mounted Robot Arm Systems
Shintemirov, A., Takhanov, R., Yessenbayev, Z., Daribayev, Z., Sandygulova, A. & Rubagotti, M.
1/1/22 → 12/31/24
Project: CRP
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E-skin: Neuromorphic Tactile Skin for Intelligent Robot – Environment and Robot - Human Physical Interaction
1/1/22 → 12/31/24
Project: FDCRGP
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Development of an Intrinsically Safe Actuation System with Adaptive Neuromorphic Control for Humanoid Robotics Application
Folgheraiter, M., Gini, G. & Rubagotti, M.
1/1/21 → 12/31/23
Project: FDCRGP
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Stochastic and learning-based predictive control methods for physical human-robot interaction.
Rubagotti, M., Sandygulova, A., Shintemirov, A., Yessenbayev, Z. & Summers, D.
1/1/20 → 12/31/23
Project: CRP
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АР08052091: Development of an Autonomous Skid Steering Based Mobile Robot-Manipulation System for Automating Warehouse Logistics Operations in Kazakhstan
Shintemirov, A., Rubagotti, M., Kruchinin, R., Oleinikov, A., Tursynbek, I., Saparova, Z., Malik, A. & Dorbekhany, Z.
1/1/20 → 12/31/22
Project: MES RK
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Scenario-based model predictive control with probabilistic human predictions for human–robot coexistence
Oleinikov, A., Soltan, S., Balgabekova, Z., Bemporad, A. & Rubagotti, M., Jan 2024, In: Control Engineering Practice. 142, 105769.Research output: Contribution to journal › Article › peer-review
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Human–robot handover with prior-to-pass soft/rigid object classification via tactile glove
Mazhitov, A., Syrymova, T., Kappassov, Z. & Rubagotti, M., Jan 2023, In: Robotics and Autonomous Systems. 159, 104311.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Shared Control of Robot Manipulators With Obstacle Avoidance: A Deep Reinforcement Learning Approach
Rubagotti, M., Sangiovanni, B., Nurbayeva, A., Incremona, G. P., Ferrara, A. & Shintemirov, A., Feb 1 2023, In: IEEE Control Systems. 43, 1, p. 44-63 20 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Adaptive super-twisting sliding mode control for maximum power point tracking of PMSG-based wind energy conversion systems
Zholtayev, D., Rubagotti, M. & Do, T. D., Jan 2022, In: Renewable Energy. 183, p. 877-889 13 p.Research output: Contribution to journal › Article › peer-review
24 Citations (Scopus) -
Deep Imitation Learning of Nonlinear Model Predictive Control Laws for Safe Physical Human-Robot Interaction
Nurbayeva, A., Shintemirov, A. & Rubagotti, M., 2022, (Accepted/In press) In: IEEE Transactions on Industrial Informatics. p. 1-12 12 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus)