Abstract
In order to increase the searching speed of map database for image feature matching, a local sub-map searching algorithm was introduced. Since many pose candidates will be generated in mobile robot localization for itself, a global localization approach with pose candidate optimization and high localization precision by using particle swarm optimization algorithm was proposed. Experiment on mobile robot Pioneer 3DX was conducted in real-world indoor environment for the analysis of the localization precision and computation time before and after pose candidate optimization. The experiment results show that the proposed approach can improve localization accuracy with a little computational cost.
| Original language | English |
|---|---|
| Pages (from-to) | 1402-1408 |
| Number of pages | 7 |
| Journal | Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) |
| Volume | 37 |
| Issue number | 6 |
| State | Published - Nov 2007 |
| Externally published | Yes |
Keywords
- Automatic control technology
- Feature matching
- Global localization
- Particle swarm optimization
- SIFT feature
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