Visual robot localization using compact binary landmarks
Visual robot localization using compact binary landmarks
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DOI：
10.1109/robot.2010.5509579
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发表时间：
2010-05
期刊：
影响因子：
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通讯作者：
Kouichirou Ikeda;Kanji Tanaka
中科院分区：
文献类型：
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作者：
Kouichirou Ikeda;Kanji Tanaka
本文研究了一种新颖的视觉地标紧凑表示法在移动机器人定位中的应用。随着在终身地图学习和信息共享网络方面的最新进展，大型地标数据库的紧凑表示变得至关重要。本文利用Web级图像检索中的语义散列技术，提出了一种紧凑的二进制编码(如32位编码)地标表示方法。我们展示了这样的二进制表示如何很好地实现了地标数据库的紧凑性，同时保持了定位系统的效率。在我们的贡献中，我们调查了成本性能、语义差距、使用所提出的技术的显著评估以及进一步减少每个地标的资源(#比特)的挑战。使用高速汽车状机器人进行的实验显示了令人振奋的结果。
This paper is concerned with the problem of mobile robot localization using a novel compact representation of visual landmarks. With recent progress in lifelong map-learning as well as in information sharing networks, compact representation of a large-size landmark database has become crucial. In this paper, we propose a compact binary code (e.g. 32bit code) landmark representation by employing the semantic hashing technique from web-scale image retrieval. We show how well such a binary representation achieves compactness of a landmark database while maintaining efficiency of the localization system. In our contribution, we investigate the cost-performance, the semantic gap, the saliency evaluation using the presented techniques as well as challenge to further reduce the resources (#bits) per landmark. Experiments using a high-speed car-like robot show promising results.