Name
Abstract | ||
|---|---|---|
This paper presents techniques developed to apply the Simultaneous Localisation and Mapping algorithm to an unmanned underwater vehicle operating in an unstructured, natural environment. It is shown that information from on-board sonar and vision sensors can be fused to select and track regions of the environment that may be used as features to estimate the vehicle's motion. Results including vehicle pose estimates and resulting environment models are shown for data acquired at the Great Barrier Reef in Australia. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICARCV.2004.1469484 | ICARCV |
Keywords | Field | DocType |
image sensors,mobile robots,motion control,position control,sensor fusion,sonar tracking,underwater vehicles,Great Barrier Reef,SLAM,on-board sonar sensor,on-board vision sensor,simultaneous localisation and mapping,underwater environment,unmanned underwater vehicle,vehicle motion estimation,vehicle pose estimates | Computer vision,Motion control,Image sensor,Computer science,Sonar,Sensor fusion,Artificial intelligence,Mobile robot,Underwater,Unmanned underwater vehicle,Underwater acoustic positioning system | Conference |
Volume | ISSN | Citations |
3 | 2474-2953 | 3 |
PageRank | References | Authors |
0.47 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ian Mahon | 1 | 94 | 6.49 |
| S. Williams | 2 | 3 | 0.47 |