Name
Abstract | ||
|---|---|---|
One of the major research directions in robotic vision focuses on SLAM using RGB-D sensors. The information can be used for decision making of robots and other areas that require precise position as a feature. This paper presents a novel algorithm to calibrate the RGB-D sensors for service robots SLAM. The distortions of the RGB and depth images are calibrated before the sensor is used as a measuring device for robot navigation. The calibration procedure includes the correction of the RGB and depth image as well as alignment of the RGB lens with the depth lens. The key advances in this paper are: a new method for RDB-D sensors calibration, and use of a depth distortion correcting model to help improve measurement precision. We experimentally verify our algorithm using varies of methods. The results show that, typically, our approach provides accurate calibration and the RGB-D sensors could provide reliable measurement information for robots navigating in unknown environments. |
Year | Venue | Field |
|---|---|---|
2015 | ICIG | Computer vision,Robot calibration,Computer science,Camera resectioning,Measurement precision,Artificial intelligence,RGB color model,Robot,Distortion,Calibration |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yue Sun | 1 | 10 | 6.00 |
| Jingtai Liu | 2 | 108 | 23.84 |
| Lei Sun | 3 | 26 | 15.36 |