Trajectories optimization of mobile robotic systems using discrete Kalman filtration

Juraj Slovak, M. Melicher, Pavol Vasek
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Abstract

The paper deals with problem of trajectories optimization of mobile robotic systems using discrete Kalman filtration (DKF). Localization and optimization of the trajectory were performed in indoor spaces using the infrared camera StarGazer. The used Mecanum omnidirectional chassis allows great maneuverability, but the movement itself causes deflection from the desired trajectory. The minimization of these deflections was solved by generally standard procedures and then we compared them with the outputs obtained with DKF. The results were quantified and evaluated at the end of the article.
基于离散卡尔曼滤波的移动机器人系统轨迹优化
利用离散卡尔曼滤波(DKF)研究移动机器人系统的轨迹优化问题。利用红外相机StarGazer在室内空间进行轨迹定位和优化。使用的Mecanum全向底盘允许很大的机动性,但运动本身会导致偏离所需的轨迹。通过一般标准程序求解这些挠度的最小化,然后将其与DKF得到的输出进行比较。在文章的最后对结果进行了量化和评价。
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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