IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Braganca, Portugal, 4 - 06 May 2016, pp.174-180
In SLAM systems, loop closures play crucial role to decrease the accumulating drift of the estimated trajectory for consistent mapping. Place recognition is so important for determining loop closure candidates. This paper presents a method for visual place recognition using image histograms in conjunction with keypoint correspondences to select loop closure candidates. The method compares color and grayscale histograms of RGB images and then applies keypoint matching to the images having similar histograms. The proposed method is integrated into a state-of-the-art RGB-D SLAM system and tested on a popular dataset. The quantitative results show that the proposed method improves accuracy significantly.