In this paper we propose a method for adaptive sampling using Unmanned Aerial Vehicles (UAVs) in oil spill management. The goal is to measure and estimate oil spill concentrations at the sea surface, while at the same time ...

Increased use of autonomy is considered crucial for continued growth in maritime industries like oil- and gas, waterborne transport, and fisheries- and aquaculture. This article presents a method called Autonomous Job ...

We consider the case of robotic bin picking of reflective steel parts, using a structured light 3D camera as a depth imaging device. In this paper, we present a new method for bin picking, based on a dual-resolution ...

Formålet med denne rapporten er å vise eksempler på bruk av fjernstyrte og autonome droner i petroleumssektoren og vise hvilke utviklingstrender innen droneteknologi som er viktige. Utfordringer og muligheter for bruk av ...

With the Yara Birkeland, the world’s first autonomous cargo ship developed for commercial use, nearing regular unmanned operation, it is crucial to assess the availability and readiness of unmanned cargo handling solutions. ...

For dynamical systems with uncertainty, robust controllers can be designed by assuming that the uncertainty is bounded. The less we know about the uncertainty in the system, the more conservative the bound must be, which ...

Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer. This makes them highly suitable for ...

Large amounts of data are typically generated in applications such as surveillance of power lines and railways, inspection of gas pipes, and security surveillance. In the latter application it is a necessity that the data ...

One challenging and not extensively studied issue in obstacle avoidance is the corner cutting problem. Avoidance constraints are usually imposed at the sampling time without regards to the intra-sample behavior of the ...