Learning the Approach During the Short-loading Cycle Using Reinforcement Learning (English)Manuscript (preprint) (Other academic)

National Category

Robotics Computer Sciences

Identifiers

URN: urn:nbn:se:ltu:diva-101851OAI: oai:DiVA.org:ltu-101851DiVA, id: diva2:1808156

Available from: 2023-10-30 Created: 2023-10-30 Last updated: 2023-11-17

In thesis

1. Towards Deep-learning-based Autonomous Navigation in the Short-loading Cycle

Open this publication in new window or tab >>Towards Deep-learning-based Autonomous Navigation in the Short-loading Cycle

Borngrund, Carl

Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.

2023 (English)Doctoral thesis, comprehensive summary (Other academic)

Place, publisher, year, edition, pages

Luleå: Luleå University of Technology, 2023

Series

Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544

National Category

Computer Sciences Robotics

Research subject

Cyber-Physical Systems

Identifiers

urn:nbn:se:ltu:diva-102486 (URN)978-91-8048-442-8 (ISBN)978-91-8048-443-5 (ISBN)

Public defence

, Luleå tekniska universitet, Luleå (English)

Supervisors

Bodin, Ulf

Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.

Sandin, Fredrik

Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.

Andreasson, Henrik

Applied Autonomous Sensor Systems, Örebro University, Örebro, Sweden.

Delsing, Jerker

Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.

Available from: 2023-11-17 Created: 2023-11-17 Last updated: 2023-11-17Bibliographically approved

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Bodin, UlfSandin, Fredrik

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