ロボティックトータルステーションによる地上真値軌跡のベンチマーク
Benchmarking ground truth trajectories with robotic total stations
移動ロボットのSLAM評価用に、ロボティックトータルステーション(RTS)とGNSSの精度・再現性を比較し、RTSがより高精度で再現性の高い地上真値を生成できることを示した。
著者: Effie Daum, Maxime Vaidis, François Pomerleau
分類: cs.RO
原文アブストラクト
Benchmarks stand as vital cornerstones in elevating SLAM algorithms within mobile robotics. Consequently, ensuring accurate and reproducible ground truth generation is vital for fair evaluation. A majority of outdoor ground truths are generated by GNSS, which can lead to discrepancies over time, especially in covered areas. However, research showed that RTS setups are more precise and can alternatively be used to generate these ground truths. In our work, we compare both RTS and GNSS systems' precision and repeatability through a set of experiments conducted weeks and months apart in the same area. We demonstrated that RTS setups give more reproducible results, with disparities having a median value of 8.6 mm compared to a median value of 10.6 cm coming from a GNSS setup. These results highlight that RTS can be considered to benchmark process for SLAM algorithms with higher precision.
