• Adaptive sampling for UAV sensor network in oil spill management 

      Grøtli, Esten Ingar; Haugen, Joakim; Johansen, Tor Arne; Imsland, Lars Struen (Peer reviewed; Journal article, 2021)
      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 ...
    • Adaptive Underwater Robotic Sampling of Dispersal Dynamics in the Coastal Ocean 

      Berget, Gunhild Elisabeth; Eidsvik, Jo; Alver, Morten; Py, Frédéric; Grøtli, Esten Ingar; Johansen, Tor Arne (Chapter, 2022)
      To get a better understanding of the highly nonlinear processes driving the ocean, efficient and informative sampling is critical. By combining robotic sampling with ocean models we are able to choose informative sampling ...
    • Autonomous Job Analysis: A Method for Design of Autonomous Marine Operations 

      Grøtli, Esten Ingar; Vagia, Marialena; Fjerdingen, Sigurd Aksnes; Bjerkeng, Magnus Christian; Transeth, Aksel Andreas; Svendsen, Eirik; Rundtop, Per (Journal article, 2016)
      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 ...
    • Bin Picking of Reflective Steel Parts Using a Dual-Resolution Convolutional Neural Network Trained in a Simulated Environment 

      Dyrstad, Jonatan Sjølund; Bakken, Marianne; Grøtli, Esten Ingar; Schulerud, Helene; Mathiassen, John Reidar Bartle (Chapter, 2019)
      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 ...
    • Bin Picking of Reflective Steel Parts Using a Dual-Resolution Convolutional Neural Network Trained in a Simulated Environment 

      Dyrstad, Jonatan Sjølund; Bakken, Marianne; Grøtli, Esten Ingar; Schulerud, Helene; Mathiassen, John Reidar Bartle (Chapter, 2019-12-15)
      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 ...
    • Bin Picking of Reflective Steel Parts using a Dual-Resolution Convolutional Neural Network Trained in a Simulated Environment 

      Dyrstad, Jonatan Sjølund; Bakken, Marianne; Grøtli, Esten Ingar; Schulerud, Helene; Mathiassen, John Reidar Bartle (Journal article; Peer reviewed, 2018-12-12)
      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 ...
    • Bruk av droner i nordområdene 

      Bakken, Trond; Johnsen, Stig Ole; Holmstrøm, Sture; Merz, Mariann; Transeth, Aksel Andreas; Grøtli, Esten Ingar; Risholm, Petter; Storvold, Rune (SINTEF rapport;2019:01284, Research report, 2019)
      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 ...
    • Canvas as a Design Tool for Autonomous Operations: : With application to net inspection of a sea based fish farm using an underwater vehicle 

      Grøtli, Esten Ingar; Bjerkeng, Magnus Christian; Rundtop, Per; Vagia, Marialena; Bakkevig, Fredrik; Transeth, Aksel Andreas (Journal article; Peer reviewed, 2017)
      Several design methods and principles have been proposed in the literature in order to guide the design of autonomous operations. Putting the required efforts into learning and using the methods is a daunting task, and ...
    • Dronen gjorde jobben 

      Grøtli, Esten Ingar (Others, 2015-02-23)
    • Exact and over-approximated guarantees for corner cutting avoidance in a multi-obstacle environment 

      Grøtli, Esten Ingar; Stoican, Florin; Prodan, Ionela (Journal article; Peer reviewed, 2018)
      The corner cutting avoidance problem is an important but often overlooked part of motion planning strategies. Obstacle and collision avoidance constraints are usually imposed at the sampling time without regards to the ...
    • A gap analysis for automated cargo handling operations with geared vessels frequenting small sized ports 

      Merz, Mariann; Grøtli, Esten Ingar; Mørkrid, Odd Erik; Tangstad, Espen Johansen; Fossøy, Synne; Nordahl, Håvard (Journal article; Peer reviewed, 2023)
      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. ...
    • Kartlegging av status og potensiale for dronebasert teknologi. Anvendelser innen naturfare og infrastruktur 

      Grøtli, Esten Ingar; Transeth, Aksel Andreas; Gylland, Anders Samstad; Risholm, Petter; Bergh, Ida Soon Brøther (SINTEF Rapport;, Research report, 2014)
      NIFS (Naturfare, Infrastruktur, Flom og Skred) er et felles satsingsområde mellom etatene Jernbaneverket, Norges vassdrags- og energidirektorat og Statens vegvesen. På vegne av NIFS har SINTEF utført en kartlegging av ...
    • Learning-based Robust Model Predictive Control for Sector-bounded Lur'e Systems 

      Seel, Katrine; Haring, Mark A. M.; Grøtli, Esten Ingar; Pettersen, Kristin Ytterstad; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2021)
      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 ...
    • A Levenberg-Marquardt Algorithm for Sparse Identification of Dynamical Systems 

      Haring, Mark A. M.; Grøtli, Esten Ingar; Riemer-Sørensen, Signe; Seel, Katrine; Hanssen, Kristian Gaustad (Peer reviewed; Journal article, 2022)
      Low complexity of a system model is essential for its use in real-time applications. However, sparse identification methods commonly have stringent requirements that exclude them from being applied in an industrial setting. ...
    • Linear Antisymmetric Recurrent Neural Networks 

      Moe, Signe; Remonato, Filippo; Grøtli, Esten Ingar; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2020)
      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 ...
    • Mid-Level MPC and 6 DOF Output Path Following for Robotic Manipulators 

      Arbo, Mathias Hauan; Grøtli, Esten Ingar; Gravdahl, Jan Tommy (Journal article; Peer reviewed, 2017)
      In this article we discuss some of the benefits of using an MPC as a mid-level controller between the path generator and the low-level joint controller of a robot system. The MPC handles rudimentary runtime constraints ...
    • Motion- and Communication-Planning of Unmanned Aerial Vehicles in Delay Tolerant Network using Mixed-Integer Linear Programming 

      Grøtli, Esten Ingar; Johansen, Tor Arne (Journal article; Peer reviewed, 2016)
      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 ...
    • Neural Network-based Model Predictive Control with Input-to-State Stability 

      Seel, Katrine; Grøtli, Esten Ingar; Moe, Signe; Gravdahl, Jan Tommy; Pettersen, Kristin Ytterstad (Peer reviewed; Journal article, 2021)
      Learning-based controllers, and especially learning-based model predictive controllers, have been used for a number of different applications with great success. In spite of good performance, a lot of these cases lack ...
    • On corner cutting in multi-obstacle avoidance problems 

      Stoican, Florin; Grøtli, Esten Ingar; Prodan, Ionela; Oara, Cristian (Journal article, 2015)
      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 ...
    • On Model Predictive Path Following and Trajectory Tracking for Industrial Robots 

      Arbo, Mathias Hauan; Grøtli, Esten Ingar; Gravdahl, Jan Tommy (Journal article; Peer reviewed, 2017)
      In this article the model predictive path following controller and the model predictive trajectory tracking con-troller are compared for a robotic manipulator. We consider both the Runge-Kutta and collocation based ...