Name
Abstract | ||
|---|---|---|
Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3390/s120709386 | SENSORS |
Keywords | Field | DocType |
AUV,mechanical scanning imaging sonar,FastSLAM | Maximum likelihood,Sonar,Electronic engineering,Artificial intelligence,Simultaneous localization and mapping,Resampling,Sea trial,Computer vision,Simulation,Data association,Engineering,Robot,Underwater | Journal |
Volume | Issue | ISSN |
12 | 7.0 | 1424-8220 |
Citations | PageRank | References |
14 | 1.11 | 23 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo He | 1 | 77 | 13.20 |
| Yan Liang | 2 | 14 | 1.11 |
| Xiao Feng | 3 | 14 | 1.44 |
| Rui Nian | 4 | 159 | 12.18 |
| Tianhong Yan | 5 | 24 | 2.86 |
| Minghui Li | 6 | 16 | 1.66 |
| Shujing Zhang | 7 | 14 | 1.44 |