• Discretization and Representation of a Complex Environment for On-Policy Reinforcement Learning for Obstacle Avoidance for Simulated Autonomous Mobile Agents 

      Jansson, Andreas Dyrøy (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-12)
      In recent years, the demand for digitalization, automation, and smart systems in the airline industry has accelerated. Furthermore, due to the ongoing global pandemic as of 2022, airlines are faced with the challenge of offering flexibility in both cargo and passenger capacity. Studies show that the use of smart products and autonomous agents are expected to play a key part in the digital transformation ...
    • Irregular luggage classification experiments using data from Tromsø airport 

      Jansson, Andreas Dyrøy; Bremdal, Bernt Arild; Remman, Espen (Chapter; Bokkapittel, 2023-09-22)
      This paper examines the current state-of-the-art in object tracking and detection in the context of baggage handling systems using a variety of technologies, with special interest in image classification. Data collection at Tromsø Airport using simple and inexpensive equipment in order to capture images of different types of luggage will be described. Furthermore, a selection of three relevant ...
    • User-Friendly MES Interfaces: Recommendations for an AI-Based Chatbot Assistance in Industry 4.0 Shop Floors 

      Mantravadi, Soujanya; Jansson, Andreas Dyrøy; Møller, Charles (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-04)
      The purpose of this paper is to study an Industry 4.0 scenario of ‘technical assistance’ and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer ...