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Binocular Vision Pose Estimation Based on PSOPF

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Published under licence by IOP Publishing Ltd
, , Citation Yu Fei et al 2019 J. Phys.: Conf. Ser. 1302 032051 DOI 10.1088/1742-6596/1302/3/032051

1742-6596/1302/3/032051

Abstract

In order to realize robot autonomous localization and navigation, binocular vision localization based on particle swarm optimized particle filter (PSOPF) is put forward according to the characteristics of nonlinear and non-Gaussian distribution complex system. The localization of 6-DOF robot only depends on binocular vision in the method. At first, road signs are obtained by SIFT feature matching points of binocular vision. The second, initial pose estimation is obtained by four elements. Finally, robot pose is estimated accurately by PSOPF, and the algorithm overco mes the shortcoming of particle filter (PF) and imp rove estimation accuracy. Experiment results show that this algorithm has high computing accuracy and robustness.

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10.1088/1742-6596/1302/3/032051