现代视觉SLAM方法的评价

2015 Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT) Pub Date : 2015-11-01 DOI:10.1109/AINL-ISMW-FRUCT.2015.7382963

Arthur Huletski, D. Kartashov, K. Krinkin

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引用次数: 33

摘要

同时定位与映射(SLAM)是机器人领域的一个具有挑战性的课题。研究人员在这方面努力工作，因此每年都会发表一些新的SLAM算法以及对已知算法的改进。我们选择了近期(2013-中期)。2015)理论上可以在移动机器人上运行的方法并对其进行评估。本文对ORB-SLAM、LSD-SLAM、L-SLAM和OpenRatSLAM算法进行了简单直观的描述，并对这些算法进行了理论比较(基于给定的描述)，并用TUM RGB-D基准进行了评价。

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Evaluation of the modern visual SLAM methods

Simultaneous Localization and Mapping (SLAM) is a challenging task in robotics. Researchers work hard on it, so several novel SLAM algorithms as well as enhancements for the known ones are published every year. We have selected recent (2013-mid. 2015) approaches that in theory can be run on mobile robot and evaluated it. This paper gives brief intuitive description of ORB-SLAM, LSD-SLAM, L-SLAM and OpenRatSLAM algorithms, then compares the algorithms theoretically (based on given description) and evaluates them with TUM RGB-D benchmark.

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来源期刊

2015 Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT)

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