This organisation features resources of CBGL, the Cumulative-Absolute-Error-per-Ray-based Global Localisation method. CBGL may localise a 2D LIDAR sensor in a map of its environment given only one LIDAR measurement and the map.
- cbgl contains the
roscppsource code anddocker-related files for building and deploying it - IROS-2024-paper contains the source
texcode of the paper titled "CBGL: Fast Monte Carlo Passive Global Localisation of 2D LIDAR Sensor", accepted at the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, held at Abu Dhabi, UAE - IROS-2024-presentations-resources contains material for presenting CBGL, namely the poster and pitch required by IROS 2024, CBGL in graphical abstract form, its full presentation, and video illustration of its methodology and key properties
- ros-experiments-src contains the source
C++code of CBGL as well as that of state-of-the-art methods that was used to test the methods' performance in global localisation withROS, featured in the experimental evaluation section of the paper - sim-experiments-src contains the source
C++code of CBGL that was used to test its performance in global localisation with respect to varying scan--to--scan-matching methods and environment area, featured in the experimental evaluation and limitations sections of the paper - experiments-logs contains raw data used to illustrate and support CBGL's contributions in the experimental evaluation, and characterisation and limitations sections of the paper