Panoramic View-Based Navigation in Outdoor Environments Based on Support Vector Learning
Panoramic View-Based Navigation in Outdoor Environments Based on Support Vector Learning
复制标题
基于支持向量学习的户外环境全景导航
DOI：
10.1109/iros.2006.282636
复制
发表时间：
2006
期刊：
影响因子：
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通讯作者：
Y. Shirai
中科院分区：
文献类型：
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作者：
Hideo Morita;M. Hild;J. Miura;Y. Shirai
本文描述了一种在室外环境中基于全景视图的导航。我们一直在开发一种两阶段导航方法。在训练阶段，机器人获取图像序列沿着所需的路线，并自动学习的路线视觉。在随后的自主导航阶段中，机器人通过将输入图像与所学习的路线表示进行比较来定位自身。为了对天气和季节的变化具有鲁棒性，采用了基于对象的比较。我们以前的方法采用支持向量机（SVM）算法的对象识别和定位，表现出令人满意的性能，但有时是敏感的变化的机器人的航向。因此，本文扩展的方法，使用全景图像。通过在图像中搜索与模型图像最匹配的区域，可以大大提高定位性能，为机器人提供全局正确的运动方向
This paper describes a panoramic view-based navigation in outdoor environments. We have been developing a two-phase navigation method. In the training phase, the robot acquires image sequences along the desired route and automatically learns the route visually. In the subsequent autonomous navigation phase, the robot moves by localizing itself by comparing input images with the learned route representation. To be robust to changes of weather and seasons, an object-based comparison is adopted. Our previous method applied a support vector machine (SVM) algorithm to object recognition and localization and exhibited a satisfactory performance but was sometimes sensitive to the variation of the robot's heading. This paper thus extends the method to use panoramic images. By searching the image for the region which matches the model image the most, a new method can considerably improve the localization performance and provide the robot with globally correct directions to move
DOI：
10.1109/iros.2003.1249323
发表时间：
2003-10
期刊：
Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453)
影响因子：
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作者：
Hiroaki Katsura;J. Miura;M. Hild;Y. Shirai
通讯作者：
Hiroaki Katsura;J. Miura;M. Hild;Y. Shirai