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Blar i NTNU Open på forfatter "Lekkas, Anastasios M."

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Viser treff 1-12 av 12

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    • A Voronoi-diagram-based dynamic path-planning system for underactuated marine vessels 

      Candeloro, Mauro; Lekkas, Anastasios M.; Sørensen, Asgeir Johan (Journal article; Peer reviewed, 2017)
      The main contribution of this paper is the development of a rapid, dynamic path-planning system for 3-DOF marine surface vessels navigating in environments where other marine vehicles might be operating too. The method is ...
    • Autonomous docking using direct optimal control 

      Martinsen, Andreas Bell; Lekkas, Anastasios M.; Gros, Sebastien (Journal article; Peer reviewed, 2019)
      We propose a method for performing autonomous docking of marine vessels using numerical optimal control. The task is framed as a dynamic positioning problem, with the addition of spatial constraints that ensure collision ...
    • Curved Path Following with Deep Reinforcement Learning: Results from Three Vessel Models 

      Martinsen, Andreas Bell; Lekkas, Anastasios M. (Chapter, 2018)
      This paper proposes a methodology for solving the curved path following problem for underactuated vehicles under unknown ocean current influence using deep reinforcement learning. Three dynamic models of high complexity ...
    • Dynamic Wireless Charging of Autonomous Vehicles: Small-scale demonstration of inductive power transfer as an enabling technology for self-sufficient energy supply 

      Guidi, Giuseppe; Lekkas, Anastasios M.; Stranden, Jon Eivind; Suul, Jon Are Wold (Peer reviewed; Journal article, 2020)
      Recent developments toward selfdriving cars combined with technology for wireless inductive power transfer can enable electric vehicles that are fully autonomous with respect to operation and energy requirements. Furthermore, ...
    • Energy-Optimized Path Planning for Autonomous Ferries 

      Bitar, Glenn Ivan; Breivik, Morten; Lekkas, Anastasios M. (Journal article, 2018)
      The topic of energy-optimized path planning using pseudospectral optimal control is considered. An optimal control problem (OCP) is formulated to produce an energy-optimized path between two points among static obstacles. ...
    • Guidance and Path-Planning Systems for Autonomous Vehicles 

      Lekkas, Anastasios M. (Doktoravhandlinger ved NTNU, 1503-8181; 2014:126, Doctoral thesis, 2014)
      This thesis is concerned with two interconnected and very important problems regarding the autonomy of vehicles, namely, path planning and guidance. By adopting a modular approach, path planning and guidance can be viewed ...
    • Hybrid Collision Avoidance for ASVs Compliant with COLREGs Rules 8 and 13-17 

      Eriksen, Bjørn-Olav Holtung; Bitar, Glenn Ivan; Breivik, Morten; Lekkas, Anastasios M. (Journal article; Peer reviewed, 2020)
      This paper presents a three-layered hybrid collision avoidance (COLAV) system for autonomous surface vehicles, compliant with rules 8 and 13–17 of the International Regulations for Preventing Collisions at Sea (COLREGs). ...
    • Online Path Planning for Surface Vehicles Exposed to Unknown Ocean Currents Using Pseudospectral Optimal Control 

      Lekkas, Anastasios M.; Roald, Ann Louise; Breivik, Morten (Journal article; Peer reviewed, 2016)
      This paper investigates the feasibility of using pseudospectral (PS) optimal control in real-time path planning for marine surface vehicles in environments where both obstacles and unknown disturbances are present. In ...
    • Optimization-Based Automatic Docking and Berthing of ASVs Using Exteroceptive Sensors: Theory and Experiments 

      Martinsen, Andreas Bell; Bitar, Glenn Ivan; Lekkas, Anastasios M.; Gros, Sebastien (Peer reviewed; Journal article, 2020)
      Docking of autonomous surface vehicles (ASVs) involves intricate maneuvering at low speeds under the influence of unknown environmental forces, and is often a challenging operation even for experienced helmsmen. In this ...
    • Reinforcement Learning-Based Tracking Control of USVs in Varying Operational Conditions 

      Martinsen, Andreas Bell; Lekkas, Anastasios M.; Gros, Sebastien (Peer reviewed; Journal article, 2020)
      We present a reinforcement learning-based (RL) control scheme for trajectory tracking of fully-actuated surface vessels. The proposed method learns online both a model-based feedforward controller, as well an optimizing ...
    • Straight-Path Following for Underactuated Marine Vessels using Deep Reinforcement Learning 

      Martinsen, Andreas Bell; Lekkas, Anastasios M. (Chapter, 2018)
      We propose a new framework, based on reinforcement learning, for solving the straight-path following problem for underactuated marine vessels under the influence of unknown ocean current. A dynamic model from the Marine ...
    • Warm-Started Optimized Trajectory Planning for ASVs 

      Bitar, Glenn Ivan; Vestad, Vegard Nitter; Lekkas, Anastasios M.; Breivik, Morten (Journal article; Peer reviewed, 2019)
      We consider warm-started optimized trajectory planning for autonomous surface vehicles (ASVs) by combining the advantages of two types of planners: an A* implementation that quickly finds the shortest piecewise linear path, ...

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