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没有定位的地图构建降维技术Map Building without Localization by Dimensionality Reduction Techniques |
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| 课程网址: | http://videolectures.net/icml07_yairi_bwlc/ |
| 主讲教师: | Takehisa Yairi |
| 开课单位: | 东京大学 |
| 开课时间: | 2007-06-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This paper proposes a new map building framework for mobile robot named Localization-Free Mapping by Dimensionality Reduction (LFMDR). In this framework, the robot map building is interpreted as a problem of reconstructing the 2-D coordinates of ob jects so that they maximally preserve the local proximity of the ob jects in the space of robot's observation history. Not only traditional linear PCA but also recent manifold learning techniques can be used for solving this problem. In contrast to the SLAM framework, LFMDR framework does not require localization procedures nor explicit measurement and motion models. In the latter part of this paper, we will demonstrate "visibility-only" and "bearing-only" localization-free mappings which are derived by applying LFMDR framework to the visibility and bearing measurements respectively. |
| 关 键 词: | 机器学习; 预处理; 机器人构建地图; 降维映射 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-24：yumf |
| 阅读次数: | 63 |