9 April 2018 Multicamera polarized vision for the orientation with the skylight polarization patterns
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Abstract
A robust orientation algorithm based on the skylight polarization patterns for the urban ground vehicle is presented. We present the orientation model with the Rayleigh scattering and propose the robust orientation algorithm with the total least square. The proposed algorithm can utilize the whole sky area polarization patterns for realizing a more robust and accurate orientation. To enhance the algorithm’s robustness in the urban environment, we develop a real-time method that uses the gradient of the degree of the polarization to remove the obstacles in the polarization image. In addition, our algorithm can solve the ambiguity problem of the polarized orientation without any other sensors. We also conduct a static rotating and a dynamic car experiments to evaluate the algorithm. The results demonstrate that our proposed algorithm can provide an accurate orientation estimation for the ground vehicle in the open and urban environments—the root-mean-square error in the static experiment is 0.28 deg and in the dynamic experiment is 0.81 deg. Finally, we discuss insights gained with respect to further work in optics and robotics.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Chen Fan, Xiaoping Hu, Xiaofeng He, Lilian Zhang, Yujie Wang, "Multicamera polarized vision for the orientation with the skylight polarization patterns," Optical Engineering 57(4), 043101 (9 April 2018). https://doi.org/10.1117/1.OE.57.4.043101 Submission: Received 5 December 2017; Accepted 21 March 2018
Submission: Received 5 December 2017; Accepted 21 March 2018
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