Martin Magnusson

Researcher and lecturer with the Mobile Robotics & Olfaction lab of AASS.

Research Interests

My main research is concerned with 3D perception, and efficient and versatile 3D surface representations. I have investigated 3D scan registration and mobile-robot applications such as localisation, loop detection, and semantic analysis of 3D scenes. I have also been investigating methods for using 3D perception in autoloading of piled materials in construction and mining applications.

Since recently, my research also includes mapping methods that go beyond mere geometry, and methods for making use of maps with high uncertainty. I have a particular interest in quantitative quality measures of maps and the methods that are used when constructing them.

I support the international committee for robot arms control and the campaign to stop autonomous military robots.


I teach Probabilistic Robotics, Computer Graphics, and Imperative Programming. I am also coordinating our Master's Programme in Robotics and Intelligent Systems.

Selected publications


This list of publications is updated intermittently. For a more complete list of papers, please also refer to my Google Scholar profile. You can also follow me on ResearchGate.

Journal articles

Conference papers

Workshop papers




This section contains links to 3D scan data used for the experimental results in the publications listed above. See also the Osnabrück Robotic 3D Scan Repository, which contains some of the data sets used here.


This section contains precompiled releases of some of the software used for the results in my publications. Source code is available on request.

Brief CV

I currently work as lektor (asst. prof.) in the Mobile Robotics & Olfaction lab of AASS. I am mainly involved in the SmokeBot and AIR projects, working with methods for making use of rough and heterogeneous prior information in SLAM.

I am vice chair of the IEEE/RAS Working Group for the IEEE standard 1873-2015 for representing map data for robot navigation.

Previously I have also been active in the SPENCER project, working with safe and robust localisation and mapping in a crowded environment. I was leading the ALLO project (with partners Volvo Construction Equipment and NCC) and was also heavily involved in its predecessor ALL-4-eHAM. The target application in both of these projects was autonomous wheel loaders.

In 2009, I received a tekn. dr. (Ph. D.) degree from Örebro University. Between 2004 and 2009, I was an industrial graduate student at Örebro University in cooperation with Atlas Copco Rock Drills. The focus of my research as a PhD student was the 3D normal-distributions transform and its applications for scan registration, surface analysis, and loop detection.

I received my undergraduate education in computer science at Uppsala University, interleaved with periods of work and play. I wrote my Master's thesis on the subject of hierarchical reinforcement learning for balancing a bipedal robot, and received my fil. mag. (M. Sc.) in computer science from Uppsala University in 2004.


Martin Magnusson
School of Science and Technology, Örebro University,
SE - 70182 Örebro, Sweden
Room: T-1216
Phone: (+46/0) 19 - 303870
Fax: (+46/0) 19 - 303463
Email (masked to avoid spamming): martin {dot} magnusson {at} oru {dot} se


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