Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark...Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark cannot be seen. The use of multiple marks can solve this problem. However, the extra process to design and identify different marks will significantly increase system complexity. In this paper, a novel vision-based locating method is proposed by using marks with feature points arranged in a radial shape. The feature points of the marks consist of inner points and outer points. The positions of the inner points are the same in all marks, while the positions of the outer points are different in different marks. Unlike traditional camera locating methods （the PnP methods）, the proposed method can calculate the camera location and the positions of the outer points simultaneously. Then the calculation results of the positions of the outer points are used to identify the mark. This method can make navigation with multiple marks more efficient. Simulations and real world experiments are carried out, and their results show that the proposed method is fast, accurate and robust to noise.展开更多
基金supported by National Basic Research Program of China (No.2010CB731800)
文摘Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark cannot be seen. The use of multiple marks can solve this problem. However, the extra process to design and identify different marks will significantly increase system complexity. In this paper, a novel vision-based locating method is proposed by using marks with feature points arranged in a radial shape. The feature points of the marks consist of inner points and outer points. The positions of the inner points are the same in all marks, while the positions of the outer points are different in different marks. Unlike traditional camera locating methods （the PnP methods）, the proposed method can calculate the camera location and the positions of the outer points simultaneously. Then the calculation results of the positions of the outer points are used to identify the mark. This method can make navigation with multiple marks more efficient. Simulations and real world experiments are carried out, and their results show that the proposed method is fast, accurate and robust to noise.
