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Martin Magnusson

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

Email: martin.magnusson@oru.se

Phone: +46 19 303870

Room: T1222

Research subject

Computer Science

Research environments

About Martin Magnusson

I am a researcher with the Mobile Robotics and Olfaction lab at the AASS research centre.

Research

My main research is concerned with localisation and mapping with 3D perception for mobile robots, and in particular efficient and versatile 3D surface representations. In the past 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.

More 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, as well as maps of dynamics and flow, and the use of heterogeneous map data (e.g. hand-drawn sketh maps) In robotics.

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 well 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.

Teaching

I teach Computer Graphics and Imperative Programming.

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Active projects

Completed projects

Research groups

Mobile Robotics and Olfaction Lab

Publications

Articles in journals

Adolfsson, D. , Magnusson, M. , Alhashimi, A. , Lilienthal, A. & Andreasson, H. (2023). Lidar-Level Localization With Radar? The CFEAR Approach to Accurate, Fast, and Robust Large-Scale Radar Odometry in Diverse Environments. IEEE Transactions on robotics, 39 (2), 1476-1495.
Kucner, T. P. , Magnusson, M. , Mghames, S. , Palmieri, L. , Verdoja, F. , Swaminathan, C. S. , Krajnik, T. , Schaffernicht, E. & et al. (2023). Survey of maps of dynamics for mobile robots. The international journal of robotics research.
Adolfsson, D. , Karlsson, M. , Kubelka, V. , Magnusson, M. & Andreasson, H. (2023). TBV Radar SLAM - Trust but Verify Loop Candidates. IEEE Robotics and Automation Letters, 8 (6), 3613-3620.
Molina, S. , Mannucci, A. , Magnusson, M. , Adolfsson, D. , Andreasson, H. , Hamad, M. , Abdolshah, S. , Chadalavada, R. T. & et al. (2023). The ILIAD Safety Stack: Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots. IEEE robotics & automation magazine.
Swaminathan, C. S. , Kucner, T. P. , Magnusson, M. , Palmieri, L. , Molina, S. , Mannucci, A. , Pecora, F. & Lilienthal, A. J. (2022). Benchmarking the utility of maps of dynamics for human-aware motion planning. Frontiers in Robotics and AI, 9.
Adolfsson, D. , Castellano-Quero, M. , Magnusson, M. , Lilienthal, A. J. & Andreasson, H. (2022). CorAl: Introspection for robust radar and lidar perception in diverse environments using differential entropy. Robotics and Autonomous Systems, 155.
Brandão, M. , Mansouri, M. & Magnusson, M. (2022). Editorial: Responsible Robotics. Frontiers in Robotics and AI, 9.
Luperto, M. , Kucner, T. P. , Tassi, A. , Magnusson, M. & Amigoni, F. (2022). Robust Structure Identification and Room Segmentation of Cluttered Indoor Environments From Occupancy Grid Maps. IEEE Robotics and Automation Letters, 7 (3), 7974-7981.
Alhashimi, A. , Magnusson, M. , Knorn, S. & Varagnolo, D. (2021). Calibrating Range Measurements of Lidars Using Fixed Landmarks in Unknown Positions. Sensors, 21 (1).
Gholami Shahbandi, S. & Magnusson, M. (2019). 2D map alignment with region decomposition. Autonomous Robots, 43 (5), 1117-1136.
Mielle, M. , Magnusson, M. & Lilienthal, A. J. (2019). The Auto-Complete Graph: Merging and Mutual Correction of Sensor and Prior Maps for SLAM. Robotics, 8 (2).
Gabellieri, C. , Palleschi, A. , Mannucci, A. , Pierallini, M. , Stefanini, E. , Catalano, M. G. , Caporale, D. , Settimi, A. & et al. (2019). Towards an Autonomous Unwrapping System for Intralogistics. IEEE Robotics and Automation Letters, 4 (4), 4603-4610.
Mielle, M. , Magnusson, M. & Lilienthal, A. J. (2019). URSIM: Unique Regions for Sketch Map Interpretation and Matching. Robotics, 8 (2).
Fan, H. , Kucner, T. P. , Magnusson, M. , Li, T. & Lilienthal, A. (2018). A Dual PHD Filter for Effective Occupancy Filtering in a Highly Dynamic Environment. IEEE transactions on intelligent transportation systems (Print), 19 (9), 2977-2993.
Amigoni, F. , Yu, W. , Andre, T. , Holz, D. , Magnusson, M. , Matteucci, M. , Moon, H. , Yokozuka, M. & et al. (2018). A Standard for Map Data Representation: IEEE 1873-2015 Facilitates Interoperability Between Robots. IEEE robotics & automation magazine, 25 (1), 65-76.
Almqvist, H. , Magnusson, M. , Kucner, T. P. & Lilienthal, A. (2018). Learning to detect misaligned point clouds. Journal of Field Robotics, 35 (5), 662-677.
Gholami Shahbandi, S. , Magnusson, M. & Iagnemma, K. (2018). Nonlinear Optimization of Multimodal Two-Dimensional Map Alignment With Application to Prior Knowledge Transfer. IEEE Robotics and Automation Letters, 3 (3), 2040-2047.
Kucner, T. P. , Magnusson, M. , Schaffernicht, E. , Hernandez Bennetts, V. M. & Lilienthal, A. J. (2017). Enabling Flow Awareness for Mobile Robots in Partially Observable Environments. IEEE Robotics and Automation Letters, 2 (2), 1093-1100.
Almqvist, H. , Magnusson, M. & Lilienthal, A. J. (2014). Improving Point Cloud Accuracy Obtained from a Moving Platform for Consistent Pile Attack Pose Estimation. Journal of Intelligent and Robotic Systems, 75 (1), 101-128.
Stoyanov, T. , Magnusson, M. & Lilienthal, A. J. (2013). Comparative evaluation of the consistency of three-dimensional spatial representations used in autonomous robot navigation. Journal of Field Robotics, 30 (2), 216-236.
Stoyanov, T. , Magnusson, M. , Lilienthal, A. J. & Andreasson, H. (2012). Fast and accurate scan registration through minimization of the distance between compact 3D NDT Representations. The international journal of robotics research, 31 (12), 1377-1393.
Magnusson, M. , Andreasson, H. , Nüchter, A. & Lilienthal, A. J. (2009). Automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transform. Journal of Field Robotics, 26 (11-12), 892-914.
Magnusson, M. , Lilienthal, A. J. & Duckett, T. (2007). Scan registration for autonomous mining vehicles using 3D-NDT. Journal of Field Robotics, 24 (10), 803-827.

Books

Kucner, T. P. , Lilienthal, A. , Magnusson, M. , Palmieri, L. & Swaminathan, C. S. (2020). Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots.. Springer International Publishing (Cognitive Systems Monographs 40).