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2D RGB Depth Map Building for Outdoor Mobile Robots using Particle Filter
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- Authors
- Yu-Cheol Lee, Christiand, Joochan Sohn, Sunghoon Kim
- Issue Date
- 2012-11
- Citation
- International Symposium on Computational Intelligence and Informatics (CINTI) 2012, pp.201-206
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper describes the RGB depth (RGB-D) map building for mobile robots based on accurate outdoor localization and perception sensors consisting of wheel odometer, global positioning system (GPS), and camera and laser range finder (LRF). A localization method based on Particle Filter (PF) is used to integrate the sensor data and the topological map. The sensors data include geo-locations, the relative moving positions and the traffic mark positions measured by GPS, odometer and camera. The topological map has information for converting domains between geo-and metric-locations of GPS and odometer. And it also gives the actual positions of traffic marks extracted from aerial or satellite images. In addition, we used also a 2D RGB-D map building method by matching information between RGB and depth by camera and LRF at estimated position from PF. An experiment has been performed in outdoor environment to validate the proposed method. Experimental results show the high accuracy RGB-D map that is able to use for navigation of mobile robot in outdoor environments. © 2012 IEEE.
- KSP Keywords
- Depth Map, High accuracy, Laser range finder, Localization method, Map building, Mobile robots, Outdoor environments, Outdoor localization, Particle filter (pf), Perception sensors, RGB-D