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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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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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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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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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Jing Qi, Xilun Ding, Weiwei Li, Zhonghua Han and Kun Xu
Hand postures and speech are convenient means of communication for humans and can be used in human?robot interaction. Based on structural and functional characteristics of our integrated leg-arm hexapod robot, to perform reconnaissance and rescue tasks i...
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