Comparing holistic and feature-based visual methods for estimating the relative pose of mobile robots
Comparing holistic and feature-based visual methods for estimating the relative pose of mobile robots
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DOI：
10.1016/j.robot.2016.12.001
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发表时间：
2017-03-01
影响因子：
4.3
通讯作者：
Moeller, Ralf
中科院分区：
文献类型：
--
作者：
Fleer, David;Moeller, Ralf
基于特征的方法和整体方法提出了两种根本不同的方法来从成对的相机图像中进行相对姿势估计。到目前为止，文献中还缺乏这些方法之间的直接比较。这使得评估它们在移动机器人领域的许多应用的相对优点变得困难。在这项工作中，我们在自主家用清洁机器人的背景下比较了这些方法的选择。我们发现整体 Min-Warping 方法可以提供良好且快速的结果。一些基于特征的方法可以提供出色且稳健的结果，但速度要慢得多。其他此类方法也能实现高速，但对光照变化的鲁棒性降低。我们还提供新颖的图像数据库和支持数据供公众使用。 (C) 2016 Elsevier B.V. 保留所有权利。
Feature-based and holistic methods present two fundamentally different approaches to relative-pose estimation from pairs of camera images. Until now, there has been a lack of direct comparisons between these methods in the literature. This makes it difficult to evaluate their relative merits for their many applications in mobile robotics. In this work, we compare a selection of such methods in the context of an autonomous domestic cleaning robot. We find that the holistic Min-Warping method gives good and fast results. Some of the feature-based methods can provide excellent and robust results, but at much slower speeds. Other such methods also achieve high speeds, but at reduced robustness to illumination changes. We also provide novel image databases and supporting data for public use. (C) 2016 Elsevier B.V. All rights reserved.