Relevant positioning of a mobile robot using a particle filter design approach

Takoua Grami, A. Tlili
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Abstract

The present paper proposes a new framework based on a python code using the particle filter approach to monitor and estimate accurately the positions and the directions of a mobile robot. As a matter of fact, the real time localization of such a mobile robot is a challenging task due to diversified uncertainties and temporal changes in the environmental circumstances, measurement noises as well as errors of sensors used for anticipating the trajectory. The efficacy and the outstanding performances of the proposed particle filter-based real time localization approach are demonstrated via numerical simulation on an intelligent autonomous mobile robot with a considerable developed python code.
移动机器人的相关定位采用了粒子滤波的设计方法
本文提出了一种基于python代码的新框架,利用粒子滤波方法对移动机器人的位置和方向进行精确的监测和估计。事实上,由于环境环境的各种不确定性和时间变化,测量噪声以及用于预测轨迹的传感器的误差,这种移动机器人的实时定位是一项具有挑战性的任务。基于粒子滤波的实时定位方法的有效性和卓越性能通过一个智能自主移动机器人的数值仿真得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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