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Jianjun Ni, Li Wang, Xiaotian Wang and Guangyi Tang
The visual simultaneous localization and mapping (SLAM) method under dynamic environments is a hot and challenging issue in the robotic field. The oriented FAST and Rotated BRIEF (ORB) SLAM algorithm is one of the most effective methods. However, the tra...
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Ruidong Zhang and Xinguang Zhang
When using deep learning networks for dynamic feature rejection in SLAM systems, problems such as a priori static object motion leading to disturbed build quality and accuracy and slow system runtime are prone to occur. In this paper, based on the ORB-SL...
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Yunpiao Cai, Weixing Qian, Jiaqi Zhao, Jiayi Dong and Tianxiao Shen
In this paper, we propose a novel visual?inertial simultaneous localization and mapping (SLAM) method for intelligent navigation systems that aims to overcome the challenges posed by dynamic or large-scale outdoor environments. Our approach constructs a ...
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Chenyang Zhang, Teng Huang, Rongchun Zhang and Xuefeng Yi
RGB-D SLAM (Simultaneous Localization and Mapping) generally performs smoothly in a static environment. However, in dynamic scenes, dynamic features often cause wrong data associations, which degrade accuracy and robustness. To address this problem, in t...
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Sheng Miao, Xiaoxiong Liu, Dazheng Wei and Changze Li
A visual localization approach for dynamic objects based on hybrid semantic-geometry information is presented. Due to the interference of moving objects in the real environment, the traditional simultaneous localization and mapping (SLAM) system can be c...
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Yakun Wu, Li Luo, Shujuan Yin, Mengqi Yu, Fei Qiao, Hongzhi Huang, Xuesong Shi, Qi Wei and Xinjun Liu
The Simultaneous Localization and Mapping (SLAM) algorithm is a hotspot in robot application research with the ability to help mobile robots solve the most fundamental problems of ?localization? and ?mapping?. The visual semantic SLAM algorithm fused wit...
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Ling Bai, Yinguo Li and Ming Cen
With the popularity of ground and airborne three-dimensional laser scanning hardware and the development of advanced technologies for computer vision in geometrical measurement, intelligent processing of point clouds has become a hot issue in artificial ...
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Junhao Cheng, Zhi Wang, Hongyan Zhou, Li Li and Jian Yao
Most Simultaneous Localization and Mapping (SLAM) methods assume that environments are static. Such a strong assumption limits the application of most visual SLAM systems. The dynamic objects will cause many wrong data associations during the SLAM proces...
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