Name
Abstract | ||
|---|---|---|
We consider the problem of creating a consistent alignment of multiple 3D submaps containing distinctive visual landmarks in an unmodified environment. An efficient map alignment algorithm based on landmark specificity is proposed to align submaps. This is followed by a global minimization using the close-the-loop constraint. Landmark uncertainty is taken into account in the pairwise alignment and the global minimization process. Experiments show that the pairwise alignment of submaps with backward correction produces a consistent global 3D map. Our vision-based mapping approach using sparse 3D data is different from other existing approaches which use dense 2D range data from laser or sonar rangefinders. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/IRDS.2002.1041381 | IROS |
Keywords | Field | DocType |
localization,image matching,backward correction,3d submaps,landmark specificity,mobile robots,global minimization,computerised navigation,map alignment algorithm,vision-based mapping,computer vision,mobile robot,minimisation,stereo image processing,pairwise alignment,robot vision,intelligent systems,simultaneous localization and mapping,iris,sonar,uncertainty,constraint optimization,intelligent networks | Pairwise comparison,Computer vision,Computer science,Visual landmarks,Sonar,Vision based,Minimisation (psychology),Minification,Artificial intelligence,Landmark,Mobile robot | Conference |
Volume | ISBN | Citations |
1 | 0-7803-7398-7 | 14 |
PageRank | References | Authors |
0.86 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephen Se | 1 | 786 | 92.81 |
| D. G. Lowe | 2 | 15718 | 1413.60 |
| James J. Little | 3 | 2430 | 269.59 |