期刊論文
| 學年 | 105 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2017-04-13 |
| 作品名稱 | Enhanced Simultaneous Localization and Mapping (ESLAM) for Mobile Robots |
| 作品名稱（其他語言） | |
| 著者 | Chen-Chien Hsu; Wei-Yen Wang; Tung-Yuan Lin; Yin-Tien Wang; Teng-Wei Huang |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | International Journal of Humanoid Robotics 14(2), 1750007 |
| 摘要 | FastSLAM, such as FastSLAM 1.0 and FastSLAM 2.0, is a popular algorithm to solve the simultaneous localization and mapping (SLAM) problem for mobile robots. In real environments, however, the execution speed by FastSLAM would be too slow to achieve the objective of real-time design with a satisfactory accuracy because of excessive comparisons of the measurement with all the existing landmarks in particles, particularly when the number of landmarks is drastically increased. In this paper, an enhanced SLAM (ESLAM) is proposed, which uses not only odometer information but also sensor measurements to estimate the robot’s pose in the prediction step. Landmark information that has the maximum likelihood is then used to update the robot’s pose before updating the landmarks’ location. Compared to existing FastSLAM algorithms, the proposed ESLAM algorithm has a better performance in terms of computation efficiency as well as localization and mapping accuracy as demonstrated in the illustrated examples. |
| 關鍵字 | Simultaneous localization and mapping; SLAM; FastSLAM; particle filter; extended Kalman filter; navigation |
| 語言 | en |
| ISSN | |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | SGP |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/111862 ) |