2D RGB depth map building for outdoor mobile robots using Particle Filter

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.