Browsing NTNU Open by Author "Robinson, Haakon"
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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 ... -
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, ... -
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 ...