SLAM Hiveベンチマークスイート
The SLAM Hive Benchmarking Suite
コンテナ技術とクラスタ上での展開を活用し、数千回のマッピング実行を通じてSLAMアルゴリズムを大規模に評価できるオープンソースのベンチマーク基盤を提案・実装した。
著者: Yuanyuan Yang, Bowen Xu, Yinjie Li, Sören Schwertfeger
分類: cs.RO
原文アブストラクト
Benchmarking Simultaneous Localization and Mapping (SLAM) algorithms is important to scientists and users of robotic systems alike. But through their many configuration options in hardware and software, SLAM systems feature a vast parameter space that scientists up to now were not able to explore. The proposed SLAM Hive Benchmarking Suite is able to analyze SLAM algorithms in 1000's of mapping runs, through its utilization of container technology and deployment in a cluster. This paper presents the architecture and open source implementation of SLAM Hive and compares it to existing efforts on SLAM evaluation. Furthermore, we highlight the function of SLAM Hive by exploring some open source algorithms on public datasets in terms of accuracy. We compare the algorithms against each other and evaluate how parameters effect not only accuracy but also CPU and memory usage. Through this we show that SLAM Hive can become an essential tool for proper comparisons and evaluations of SLAM algorithms and thus drive the scientific development in the research on SLAM.
