| Citation: | AN Ping, WANG Guoping, YU Jiadong, et al. An efficient and accurate visual SLAM loop closure detection algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(1): 24-30. doi: 10.13700/j.bh.1001-5965.2019.0642(in Chinese)
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Simultaneous Localization and Mapping (SLAM) is one of the key technologies in visual navigation, and loop closure detection is a basis of SLAM. An efficient and accurate loop closure detection algorithm is proposed to solve the problem of low accuracy rate of SLAM loop closure detection. The loop closure detection algorithm consists of bag of words module, structure checking module, and tracking module. First, we design the bag of words model and structure checking module, combining local features with holistic features. The bag of words model compares the image similarities using visual words to obtain the closed-loop candidate frame. Then, structure checking module grayscales and normalizes the current image and the closed-loop candidate image. The normalized images are directly used as the patch of local feature to obtain holistic feature. Whether the closed-loop candidate frame is a valid closed loop is determined by the holistic descriptor. To address the problem that time consumption increases rapidly with the increase of image numbers, we design the tracking module to improve the computational efficiency. The comparative experiments with DBoW algorithm show that the proposed algorithm improves the accuracy by more than 20% and also has better real-time performance.
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