论文标题
评估视觉大满贯方法在不同环境中的鲁棒性
Evaluation of the Robustness of Visual SLAM Methods in Different Environments
论文作者
论文摘要
确定传感器的位置和方向相对于周围的周围，同时绘制传感器或同时定位和映射周围的环境正在迅速成为具有大量不同可能应用的嵌入式视觉的重要进步。本文对最新的开源SLAM算法进行了全面比较，主要重点是它们在不同环境环境中的表现。对所选算法进行了对公共可用数据集的评估，并针对数据集的环境进行了推论。这是我们在越野场景中测试方法的主要目标的第一阶段。
Determining the position and orientation of a sensor vis-a-vis its surrounding, while simultaneously mapping the environment around that sensor or simultaneous localization and mapping is quickly becoming an important advancement in embedded vision with a large number of different possible applications. This paper presents a comprehensive comparison of the latest open-source SLAM algorithms with the main focus being their performance in different environmental surroundings. The chosen algorithms are evaluated on common publicly available datasets and the results reasoned with respect to the datasets' environment. This is the first stage of our main target of testing the methods in off-road scenarios.
