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  • Mauro’s Group Publications

Mauro Da Lio

Full Professor of Mechanical Systems, University of Trento

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Mauro Da Lio is a Full Professor of mechanical systems at the University of Trento, Italy. His earlier research activity was modeling, simulation, and optimal control of mechanical multibody systems, particularly vehicle and spacecraft dynamics. More recently, his focus shifted to modeling human sensory-motor control with applications in health, robotics, and, mostly, intelligent vehicles.

He was involved in several EU Framework Programme 6 and 7 projects (PReVENT, SAFERIDER, interactIVe, VERITAS, AdaptIVe, No-Tremor, and SUNRISE). He coordinated the EU Horizon 2020 Dreams4Cars Research and Innovation Action, a collaborative robotics project that aimed at increasing the cognition abilities of artificial driving agents using offline simulation mechanisms broadly inspired by the human dream state (learning of forward models and offline synthesis of inverse ones).

Mauro’s Group Publications

Complex self-driving behaviors emerging from affordance competition in layered control architectures

Complex self-driving behaviors emerging from affordance competition in layered control architectures
Mauro Da Lio, Antonello Cherubini, Gastone Pietro Rosati Papini, Alice Plebe
Cognitive Systems Research (2022)
DOI | PDF

A Reinforcement Learning Approach for Enacting Cautious Behaviours in Autonomous Driving

A Reinforcement Learning Approach for Enacting Cautious Behaviours in Autonomous Driving
Gastone Pietro Rosati Papini, Alice Plebe, Mauro Da Lio, Riccardo Donà
IEEE Transactions on Intelligent Transportation Systems (2021)
DOI | PDF

A Mental Simulation Approach for Learning Neural-Network Predictive Control (in Self-Driving Cars)

A Mental Simulation Approach for Learning Neural-Network Predictive Control (in Self-Driving Cars)
Mauro Da Lio, Riccardo Donà, Gastone Pietro Rosati Papini, Francesco Biral, Henrik Svensson
IEEE Access (2020)
DOI | PDF

Modelling longitudinal vehicle dynamics with neural networks

Modelling longitudinal vehicle dynamics with neural networks
Mauro Da Lio, Daniele Bortoluzzi, Gastone Pietro Rosati Papini
Vehicle System Dynamics (2019)
DOI | PDF
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