| Depth Enhanced Visual-Inertial Odometry Based on Multi-State Constraint Kalman Filter | |
| Pang, Fumin; Chen, Zichong; Pu, Li; Wang, Tianmiao | |
| 2017 | |
| 会议名称 | 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) |
| 会议日期 | 2017-01-01 |
| 关键词 | Bandpass filters Constrained optimization Intelligent robots Position measurement Robots Uncertainty analysis Units of measurement Complementary property Computation loads Industry environment Inertial measurement unit Measurement model Optimization based methods Position estimates Unstructured environments Kalman filters |
| 卷号 | 2017-September |
| 页码 | 1761-1767 |
| 收录类别 | EI ; CPCI-S |
| URL标识 | 查看原文 |
| WOS记录号 | WOS:000426978202014 |
| 内容类型 | 会议论文 |
| URI标识 | http://www.corc.org.cn/handle/1471x/5945602 |
| 专题 | 北京航空航天大学 |
| 推荐引用方式 GB/T 7714 | Pang, Fumin,Chen, Zichong,Pu, Li,et al. Depth Enhanced Visual-Inertial Odometry Based on Multi-State Constraint Kalman Filter[C]. 见:2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). 2017-01-01. |
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