Research on location system of move-in-mud robot based on Kalman filter

Qingmei Yang, Qingxin Meng, Jianmin Sun, Zhixing Wang
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引用次数: 3

Abstract

Data fusion methods are widely used in autonomous robots' measurement system in order to acquire more comprehensive and more exact information. Move-in-mud Robot is a kind of autonomous robots, which is used to substitute for excavating hole underwater in wreck salvage by diver according to a planned trajectory. Location of the robot is one of keys in study on Move-in-mud Robot, which is the base of move according to planned trajectory. Based on the analysis of automotive robot orientation ways, location system is designed in the paper and location principle of move-in-mud robot is analyzed. Kalman filter is used to fuse redundant depth information of the robot. The fusion arithmetic is simulated and the result of simulation showed that the fusion not only improve location precision efficiently, but also improve reliability of location.
基于卡尔曼滤波的陷泥机器人定位系统研究
为了获得更全面、更精确的信息,数据融合方法在自主机器人的测量系统中得到了广泛的应用。陷泥机器人是一种自主机器人,用于代替潜水员按照规划的轨迹在水下挖洞进行沉船打捞。机器人的定位是研究泥地移动机器人的关键问题之一,它是机器人按照规划轨迹运动的基础。本文在分析汽车机器人定位方式的基础上,设计了定位系统,分析了陷泥机器人的定位原理。采用卡尔曼滤波对机器人的冗余深度信息进行融合。仿真结果表明,融合算法不仅有效地提高了定位精度,而且提高了定位的可靠性。
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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