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Martin Magnusson

Martin Magnusson Position: Senior Lecturer School/office: School of Science and Technology

Email: bWFydGluLm1hZ251c3NvbjtvcnUuc2U=

Phone: +46 19 303870

Room: T1222

Martin Magnusson
Research subject Research environments

About Martin Magnusson

I am currently heading the AASS organisational unit and research environment. I am also head of the Robot Navigation and Perception Lab within AASS.

Research

My research interests target robotics and AI, with a focus on advancing autonomous systems through innovations in 3D mapping and localisation, perception, as well as human-robot interaction. Early contributions include the development of the 3D Normal Distributions Transform (3D-NDT) and efficient methods for scan registration, localisation, and mapping in dynamic environments.

Recent work extends into radar-based mapping and navigation, as well as human-aware robots through predictive modelling in complex and shared environments. I have a particular interest in quantitative quality measures of maps and the methods that are used for constructing them, as well as maps of dynamics and flow, and the use of heterogeneous map data (e.g. hand-drawn sketch maps) in robotics.

How can we ensure robust autonomy all the way from sensing to reasoning? How can disparate sources of information be used to enhance autonomy of autonomous vehicles? How can we improve the way environment data is represented in order to facilitate more precise and more adaptive robots? 

Teaching

I currently teach a course in Computer Graphics which covers principles and practice from the algebra needed to compute where a 3D object should be projected onto the screen and the coding required to do so, through models for how light scatters at surfaces of different materials, to photo-realistic rendering with ray tracing and path tracing.

In this course we also connect to relevant research from my group and the field at large, recently including e.g. radar simulation models and neural rendering.

 

 

 2023-05-31

I disapprove of the strategic partnership between Saab and Örebro University that was signed in May 2023.

I do acknowledge that there may be channels of collaboration and research that are worthwhile pursuing also with the weapons industry, and I make no attempt to define what other researchers and academic staff should devote their work and energy to.

However, I want to make it clear that I strongly disapprove of my own research being used by the weapons industry, including Saab. In particular, I find it worrying that AI and robotics are mentioned specifically as an important part of this future collaboration. I support the International Committee for Robot Arms Control (ICRAC) and the Campaign to Stop Killer Robots, and I wish to have no part in contributing to the development of more "intelligent" or autonomous systems for military use.

This is not to say that I oppose of armed defence in general. However, the products of our weapons industry are largely being exported to countries over which we have no control, including those with a history of aggressive foreign or domestic policies. I do not believe that doing so contributes to a safer world, and I will choose to devote my time and energy to more productive purposes.

Research groups

Publications

Articles in journals |  Books |  Chapters in books |  Conference papers |  Doctoral theses, monographs |  Licentiate theses, monographs | 

Articles in journals

Books

Chapters in books

  • Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Closing Remarks. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. 143-151). . Springer. [BibTeX]
  • Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Introduction. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. 1-13). . Springer. [BibTeX]
  • Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Maps of Dynamics. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. 15-32). . Springer. [BibTeX]
  • Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Modelling Motion Patterns with Circular-Linear Flow Field Maps. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. 65-113). . Springer. [BibTeX]
  • Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Modelling Motion Patterns with Conditional Transition Map. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. 33-64). . Springer. [BibTeX]
  • Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Motion Planning Using MoDs. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. 115-141). . Springer. [BibTeX]
  • Kucner, T. P. , Magnusson, M. , Swaminathan, C. S. , Lilienthal, A. & Palmieri, L. (2020). Preface. In:  Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots (pp. vii-x). . Springer. [BibTeX]

Conference papers

Doctoral theses, monographs

Licentiate theses, monographs