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The Application of Particle Filtering in Dynamic Locating and Tracking of Intelligent Wheelchair

机译:粒子过滤在智能轮椅动态定位和跟踪中的应用

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摘要

In order to reduce dynamic positioning errors of intelligent wheelchair efficiently, this paper discusses the application of particle filter. At first, a localization algorithm of an intelligent wheelchair by using CSS ranging is proposed. Then the principle of standard particle filter was introduced and a corresponding filtering model of dynamic positioning was set up in this paper. The filtering algorithm was programmed on the intelligent wheelchair prototype which based on ARM chip as hardware platform, the experimental results showed that the filtering algorithm applied for dynamic positioning of intelligent wheelchair overcame the problem that kalman filter and extended kalman filter is weak for nonlinear state, reducing dynamic positioning error by 27.8% compared to trilateration.
机译:为了高效减少智能轮椅的动态定位误差,讨论了粒子过滤器的应用。首先,提出了通过使用CSS测距的智能轮椅的本地化算法。然后引入了标准颗粒滤波器的原理,并在本文中建立了相应的动态定位滤波模型。滤波算法对基于ARM芯片作为硬件平台的智能轮椅原型进行编程,实验结果表明,智能轮椅动态定位的过滤算法克服了卡尔曼滤波器和扩展卡尔曼滤波器对于非线性状态薄弱的问题,与三边形相比,将动态定位误差减少27.8%。

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