Blar i NTNU Open på forfatter "Robinson, Haakon"
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Deep learning assisted physics-based modeling of aluminum extraction process
Robinson, Haakon; Lundby, Erlend Torje Berg; Rasheed, Adil; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2023)Modeling complex physical processes such as the extraction of aluminum is mainly done using pure physics-based models derived from first principles. However, the accuracy of these models can often suffer due to a partial ... -
GANs enabled super-resolution reconstruction of wind field
Tran, Duy Tan; Robinson, Haakon; Rasheed, Adil; San, Omer; Tabib, Mandar; Kvamsdal, Trond (Peer reviewed; Journal article, 2020)Atmospheric flows are governed by a broad variety of spatio-temporal scales, thus making real-time numerical modeling of such turbulent flows in complex terrain at high resolution computationally unmanageable. In this ... -
GANs enabled super-resolution reconstruction of wind field
Tran, Duy Tan; Robinson, Haakon; Rasheed, Adil; San, Omer; Kvamsdal, Trond (Peer reviewed; Journal article, 2020)Atmospheric flows are governed by a broad variety of spatio-temporal scales, thus making real-time numerical modeling of such turbulent flows in complex terrain at high resolution computationally unmanageable. In this ... -
On the Piecewise Affine Representation of Neural Networks
Robinson, Haakon (Master thesis, 2019)Det kan vises at nevrale nett kan uttrykkes som stykkevise affine (PWA) funksjoner. Men, forskning har fokusert på å telle de lineære regionene, fremfor å finne den eksplitte PWA formen. Denne oppgaven fremfører en algoritme ... -
Physics guided neural networks for modelling of non-linear dynamics
Robinson, Haakon; Pawar, Suraj; Rasheed, Adil; San, Omer (Peer reviewed; Journal article, 2022)The success of the current wave of artificial intelligence can be partly attributed to deep neural networks, which have proven to be very effective in learning complex patterns from large datasets with minimal human ... -
Robust Reasoning for Autonomous Cyber-Physical Systems in Dynamic Environments
Håkansson, Anne; Saad, Aya; Sadanandan Anand, Akhil; Gjærum, Vilde Benoni; Robinson, Haakon; Seel, Katrine (Peer reviewed; Journal article, 2021)Autonomous cyber-physical systems, CPS, in dynamic environments must work impeccably. The cyber-physical systems must handle tasks consistently and trustworthily, i.e., with a robust behavior. Robust systems, in general, ... -
Safe Learning for Control using Control Lyapunov Functions and Control Barrier Functions: A Review
Sadanandan Anand, Akhil; Seel, Katrine; Gjærum, Vilde Benoni; Håkansson, Anne; Robinson, Haakon; Saad, Aya (Peer reviewed; Journal article, 2021)Real-world autonomous systems are often controlled using conventional model-based control methods. But if accurate models of a system are not available, these methods may be unsuitable. For many safety-critical systems, ... -
Sparse neural networks with skip-connections for nonlinear system identification
Lundby, Erlend Torje Berg; Robinson, Haakon; Rasheed, Adil; Halvorsen, Ivar Johan; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2023) -
Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning
Meyer, Eivind; Robinson, Haakon; Rasheed, Adil; San, Omer (Peer reviewed; Journal article, 2020)In this article, we explore the feasibility of applying proximal policy optimization, a state-of-the-art deep reinforcement learning algorithm for continuous control tasks, on the dual-objective problem of controlling an ... -
Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning
Meyer, Eivind; Robinson, Haakon; Rasheed, Adil; San, Omer (Peer reviewed; Journal article, 2020)In this article, we explore the feasibility of applying proximal policy optimization, a state-of-the-art deep reinforcement learning algorithm for continuous control tasks, on the dual-objective problem of controlling an ...