Browsing NTNU Open by Author "Dyrstad, Jonatan Sjølund"
Now showing items 1-5 of 5
-
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 ... -
Grasping virtual fish: A step towards deep learning from demonstration in virtual reality
Dyrstad, Jonatan Sjølund; Mathiassen, John Reidar Bartle (Journal article; Peer reviewed, 2018)We present an approach to robotic deep learning from demonstration in virtual reality, which combines a deep 3D convolutional neural network, for grasp detection from 3D point clouds, with domain randomization to generate ... -
Robot learning with visual processing in arbitrarily sized, high resolution volumes
Dyrstad, Jonatan Sjølund (Doctoral theses at NTNU;2023:266, Doctoral thesis, 2023)Flexible robots, capable of manipulating objects in unstructured environments under changing conditions, will lead to a paradigm shift in automation. Such robotic solutions can potentially transform entire industries ... -
Teaching a Robot to Grasp Real Fish by Imitation Learning from a Human Supervisor in Virtual Reality
Dyrstad, Jonatan Sjølund; Øye, Elling Ruud; Stahl, Annette; Mathiassen, John Reidar Bartle (Journal article, 2018)We teach a real robot to grasp real fish, by training a virtual robot exclusively in virtual reality. Our approach implements robot imitation learning from a human supervisor in virtual reality. A deep 3D convolutional ...