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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jensfelt, P. Wijk, O. Austin, D.J. Andersson, M. |
| Copyright Year | 2000 |
| Description | Author affiliation: Centre for Autonomous Syst., R. Inst. of Technol., Stockholm, Sweden (Jensfelt, P.) |
| Abstract | We study some modifications of the CONDENSATION algorithm. The case studied is feature based mobile robot localization in a large scale environment. The required sample set size for making the CONDENSATION algorithm converge properly can in many cases require too much computation. To manage with a sample set size which in the normal case would cause the CONDENSATION algorithm to break down. We study two modifications. The first strategy, called "CONDENSATION with random sampling", takes part of the sample set and spreads it randomly over the environment the robot operates in. The second strategy, called "CONDENSATION with planned sampling", places part of the sample set at planned positions based on the detected features. From the experiments we conclude that the second strategy is the best and can reduce the sample set size by at feast a factor of 40. |
| Starting Page | 2518 |
| Ending Page | 2524 |
| File Size | 621675 |
| Page Count | 7 |
| File Format | |
| ISBN | 0780358864 |
| ISSN | 10504729 |
| DOI | 10.1109/ROBOT.2000.846407 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-04-24 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mobile robots Large-scale systems Robot kinematics Computer vision Probability density function Convergence Computational complexity Sampling methods |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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