基于粒子群算法的车辆定位研究

Jorge Godoy, D. Gruyer, A. Lambert, J. Villagrá
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引用次数: 12

摘要

本文描述了一种基于生物群体行为的滤波算法的发展。该算法的主要目标是通过结合来自不同传感器(GPS、IMU、速度计等)和数字地图的数据来执行车辆定位。从这个意义上说,该算法同时考虑了多种解决方案,如粒子过滤器。该算法是利用从LIVIC的仪表车辆捕获的真实数据离线开发的。对算法的性能进行了验证,并与和EKF进行了比较,结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of an particle swarm algorithm for vehicle localization
This paper describes the development of a filter algorithm based on the behaviour of biological swarms. The main goal of the algorithm is to perform vehicle localization by combining the data from different sensors - GPS, IMU, speedometers, etc. - and digital maps. In this sense, the algorithm considers several solutions at the same time like Particles Filters. The algorithm has been developed off-line using real data captured from an instrumented vehicle at LIVIC. Performance of the algorithm has been validated and compared with and EKF with encouraging results.
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