CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry

2 code implementations • IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021 • Daniel Adolfsson, Martin Magnusson, Anas Alhashimi, Achim J. Lilienthal, Henrik Andreasson

This paper presents the accurate, highly efficient, and learning-free method CFEAR Radarodometry for large-scale radar odometry estimation.

Radar odometry Translation

Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments

no code implementations • 4 Mar 2020 • Li Sun, Daniel Adolfsson, Martin Magnusson, Henrik Andreasson, Ingmar Posner, Tom Duckett

More importantly, the Gaussian method (i. e. deep probabilistic localisation) and non-Gaussian method (i. e. MCL) can be integrated naturally via importance sampling.

SLAM auto-complete: completing a robot map using an emergency map

1 code implementation • 16 Feb 2017 • Malcolm Mielle, Martin Magnusson, Henrik Andreasson, Achim J. Lilienthal

Experiments in an office environment show that we can handle up to 70% of wrong correspondences and still get the expected result.

Robotics