PnP算法在室内定位中的应用

Pn P Solution Applied in Indoor Location

基于视觉的定位技术是近年来室内定位研究领域的热点之一,有着广泛的应用前景。针对基于视觉的定位算法中存在的定位结果稳定性不高、易受噪声干扰等问题,对国内外现有方法进行总结分析,提出一种结合空间参考点不确定性的相机位姿估计算法。采用模拟数据和真实数据分别进行测试,实验结果表明,该算法具有精度高、稳定性好等优点,平均误差在0.08 m,70%的点定位误差小于0.1 m,90%的点定位误差小于0.2 m,最大定位误差为0.3 m,达到室内定位精度的标准。

Indoor position technology based on visual is a hot spot which has a wide range of applications and broad prospects.In order to solve the problem that the robustness of the existing localization algorithm is not high,and sensitive to noise,after summing of the most recent years on indoor localization based on visual,the paper put forward a method to calculate the camera position which combines with the uncertainty of spatial reference points. Through the simulation experiment on simulated data and real scenarios,the proposed algorithm has been proven to be of high accuracy and robustness. The results show that average error in 0. 08 m,about 70%point positioning error is less than 0.1 m,and about 90% of the point error is less than 0. 2 m,maximum error is 0. 3 m,reaching the standard accuracy of indoor position.