Browsing NTNU Open by Author "Grøtli, Esten Ingar"

Now showing items 1-20 of 41

    • 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 ...

    • Anti-Slug Control Experiments Using Nonlinear Observers 

      Jahanshahi, Esmaeil; Skogestad, Sigurd; Grøtli, Esten Ingar (Journal article; Peer reviewed, 2013)
      Abstract: To prevent slug-flow on offshore oil production units, controlling a subsea pressure is the recommended solution. However, the subsea pressure is not often available as a measurement. The top-side pressure is ...

    • Automatic Calibration of Ship-mounted Cameras’ Extrinsic Parameters 

      Bjerkehagen, Daniel (Master thesis, 2023)
      Kalibrering er et sentralt tema innenfor autonome systemer som følge av at antakelsen om kalibrerte sensorer alltid er tilstede når sensordata brukes til å utvikle en modell av verden rundt det autonome systemet. Til tross ...

    • 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)
      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)
      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 (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 ...

    • Design and Control of a Torque Controllable Quadrupedal Robot - A study on the development of ASTRo 

      Ghansah, Adrian Bødtker; Thorseth, Paal Arthur Schjelderup (Master thesis, 2021)
      Interessen for gående roboter har de siste årene blitt betydelig mer fremtredende. Med flere bransjer som ønsker å benytte seg av robotikkteknologi, blir behovet for robuste, trygge og effektive robotplattformer større og ...

    • Design and Control of a Torque Controllable Quadrupedal Robot - A study on the development of ASTRo 

      Ghansah, Adrian Bødtker; Thorseth, Paal Arthur Schjelderup (Master thesis, 2021)
      Interessen for gående roboter har de siste årene blitt betydelig mer fremtredende. Med flere bransjer som ønsker å benytte seg av robotikkteknologi, blir behovet for robuste, trygge og effektive robotplattformer større og ...

    • Exponentially Stable Dynamic Walking in a Sprawling Quadruped 

      Lysø, Mads Erlend Bøe (Master thesis, 2022)
      Roboter med ben har vært et forskningsområde av økende akademisk og offentlig interesse de siste 50 årene. Roboter som evner å bevege seg robust og autonomt gjennom områder som byr på utfordringer for konvensjonelle kjøretøy ...

    • 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 ...

    • Model-based Reinforcement Learning for Variable Impedance Control 

      Anand, Akhil Sadanandan (Doctoral theses at NTNU;2023:149, Doctoral thesis, 2023)
      This thesis is a collection of research work in the area of reinforcement learning and robotic manipulation. A set of new results on reinforcement learning focusing on model-based approaches and variable impedance control ...

    • 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 ...

    • Nonlinear model-based control of two-phase flow in risers by feedback linearization 

      Jahanshahi, Esmaeil; Skogestad, Sigurd; Grøtli, Esten Ingar (Journal article, 2013)
      Active control of the production choke valve is the recommended solution to prevent severe slugging flow conditions at offshore oilfields. The slugging flow constitutes an unstable and highly nonlinear system; the gain of ...

    • Nonlinear observer design for a Greitzer compressor model 

      Backi, Christoph Josef; Gravdahl, Jan Tommy; Grøtli, Esten Ingar (Chapter, 2013)
      In this paper two different observers for a nonlinear compressor model have been developed and compared: A nonlinear observer based on a circle criterion design and an Extended Kalman Filter. Both of these observers ...

    • 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 ...