在轮式三轮车移动机器人上集成用于位置跟踪的电子罗盘

P. Chand
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引用次数: 0

摘要

利用编码器对轮式移动机器人进行航位推算是一种简单但不准确的位置估计方法。编码器的主要缺点是车轮滑动误差随着时间的推移而积累。这个问题通常通过使用额外的传感器来解决,比如指南针、陀螺仪或GPS。本文详细介绍了一种使用电子罗盘降低轮式三轮车移动机器人定位误差的相对低成本解决方案的集成和有效性。开发了一个定制的Visual Studio程序来调整电子罗盘的设置,并将其与基于Visual Studio的机器人控制系统集成。采用简单融合、线性加权融合和卡尔曼滤波融合三种方法对电子罗经航向数据与编码器里程计航向数据进行融合。简单融合和线性加权融合分别依赖于角加速度和角速度确定的参数。卡尔曼滤波利用编码器和电子罗盘的方差数据来确定最佳航向。在室内走廊环境中进行了实验,对各种融合方法进行了评价和比较。成功地减小了位置误差,并足以在走廊内定位机器人。
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Integrating an electronic compass for position tracking on a wheeled tricycle mobile robot
Dead-reckoning via encoders on wheeled-mobile robots is a simple but inaccurate method to estimate position. The major drawback of encoders is wheel slippage errors that accumulate over time. This problem is often addressed by using additional sensors such as compass, gyroscope, or GPS. This paper details the integration and effectiveness of a relatively low-cost solution using an electronic compass to reduce positioning error on a wheeled tricycle mobile robot. A customised Visual Studio program has been developed to adjust the settings of the electronic compass and integrate it with the Visual Studio based robot control system. The electronic compass heading data is fused with the encoder odometry heading data in three different ways: simple fusion, linear weighted fusion, and Kalman filter fusion. Simple fusion and linear weighted fusion rely on parameters determined from angular acceleration and angular velocity, respectively. The Kalman filter uses variance data for the encoders and electronic compass to determine an optimal heading. Experiments have been conducted in an indoor corridor environment to evaluate and compare the various fusion methods. Position error is successfully reduced and is sufficient to locate the robot within the corridor.
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