Abstract
Abstract
SLAM is a fundamental problem in robotic field and there have been many techniques on it. It is necessary to give an insight on weakness and strength of these techniques specific to the intended final application. This paper presents a study of three most common laser-based 2D SLAM techniques: Gmapping, KartoSLAM and Cartographer. Each technique was applied to construct maps combined with autonomous exploration. All the approaches have been evaluated and compared in terms of inaccuracy of constructed maps against the ground truth. In order to draw conclusions on the performance of the tested techniques, a metrics of average distance to the nearest neighbor (ADNN) was applied. Moreover, the computational load of each technique is examined.
Subject
General Physics and Astronomy
Reference14 articles.
1. Comparison of various slam systems for mobile robot in an indoor environment;Filipenko,2018
2. Consistency of the ekf-slam algorithm;Bailey,2006
3. Fastslam: A factored solution to the simultaneous localization and mapping problem;Montemerlo,2002
4. Improved techniques for grid mapping with Rao- Blackwellized particle filters;Grisetti;IEEE Trans. on Robotics,2007
5. The GraphSLAM algorithm with applications to large-scale mapping of urban structures;Thrun;Int. J. on Robotics Research,2005
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