Browse by Relators
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Number of items: 7.
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Olti Shera.
A Deep Reinforcement Learning Approach to Gain Tuning of Super-Twisting Sliding Mode Controllers.
Rel. Massimo Canale, Valentino Razza, Elisabetta Punta, Francesco Cerrito. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2026
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Matteo Cariglia.
A Unified Approach for Decision Making and Trajectory Planning for Automated Driving using Time-Varying Potential Fields in Intersections.
Rel. Massimo Canale, Francesco Cerrito, David Costa. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2025
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Desire'E Greco.
A Unified Approach for Decision Making and Trajectory Planning for Automated Driving using Time-Varying Potential Fields in Roundabouts.
Rel. Massimo Canale, Francesco Cerrito, David Costa. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2025
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David Costa.
Automated driving in low complexity scenarios through adaptive potential fields and model predictive control.
Rel. Massimo Canale, Carlo Novara, Pandeli Borodani, Francesco Cerrito. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2024
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Gianluca Intile.
Automated Valet Parking policies: from ego-based solutions to eco-system approaches.
Rel. Massimo Canale, Pandeli Borodani, Francesco Cerrito. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2024
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Hysni Seseri.
Automated Valet Parking policies: from ego-based solutions to eco-system approaches.
Rel. Massimo Canale, Pandeli Borodani, Francesco Cerrito. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2024
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Gloria Catella, Stefano Chiado' Puli.
Automated Driving systems based on Model Predictive Control and Artificial Potential Fields applied to Shuttle Buses in Restricted Areas.
Rel. Massimo Canale, Pandeli Borodani, Francesco Cerrito. Politecnico di Torino, Master of science program in Mechatronic Engineering, 2024
