Name
Abstract | ||
|---|---|---|
The maps generated by robots in real environment are usually incomplete, distorted, and noisy. The map quality is a quantitative performance measure of a robot's understanding of its environment. Map quality also helps researcher study the effects of different mapping algorithms and hardware components used. In this paper we present an algorithm to assess the quality of the map generated by the robot in terms of a ground truth map. To do that, First, localized features are calculated on the pre-evaluated map. Second, nearest neighbor of each valid local feature is searched between the map and the ground truth map. The quality of the map is defined according to the number of the features having the correspondence in the ground truth map. Three feature detectors are tested in terms of their effectiveness, these are the Harris corner detector, Hough Transform and Scale Invariant Feature Transform. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1774674.1774718 | PerMIS |
Keywords | Field | DocType |
hough transform,pre-evaluated map,feature detector,harris corner detector,ground truth map,map quality,scale invariant feature transform,valid local feature,localized feature,real environment,map quality assessment,ground truth,nearest neighbor | k-nearest neighbors algorithm,Scale-invariant feature transform,Computer vision,Feature detection,Corner detection,Pattern recognition,Computer science,Hough transform,Ground truth,Artificial intelligence,Mapping algorithm,Robot | Conference |
Citations | PageRank | References |
4 | 0.49 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Asim Imdad Wagan | 1 | 33 | 2.41 |
| Afzal Godil | 2 | 619 | 30.70 |
| Xiaolan Li | 3 | 91 | 7.14 |