Jiansheng Peng1,2,*, Dunhua Chen1, Qing Yang1, Chengjun Yang2, Yong Xu2, Yong Qin2
CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3209-3236, 2023, DOI:10.32604/cmc.2023.041898
Abstract Visual simultaneous localization and mapping (SLAM) is crucial in robotics and autonomous driving. However, traditional visual SLAM faces challenges in dynamic environments. To address this issue, researchers have proposed semantic SLAM, which combines object detection, semantic segmentation, instance segmentation, and visual SLAM. Despite the growing body of literature on semantic SLAM, there is currently a lack of comprehensive research on the integration of object detection and visual SLAM. Therefore, this study aims to gather information from multiple databases and review relevant literature using specific keywords. It focuses on visual SLAM based on object detection, covering different aspects. Firstly, it discusses… More >
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