利用到家定位功能对移动机器人进行里程计校准

Youngmok Yun, Byungjae Park, W. Chung
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引用次数: 12

摘要

由于大多数控制算法都是基于里程数信息,因此里程数校准是成功导航的第一步也是必不可少的一步。测程误差可分为系统误差和非系统误差。本文提出了一种利用家庭清洁机器人固有的家庭定位能力来校准系统误差的新方法。该方法针对差动驱动类型,利用增广扩展卡尔曼滤波(AKF)算法估计系统误差参数。我们的方法兼具线上和线下的特点。通过仿真和实验对该方法进行了评价,结果表明,该方法可将测程误差降低数倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Odometry calibration using home positioning function for mobile robot
Odometry calibration is a first and essential step to do for a successful navigation because most of control algorithms are based on odomety information. Odometry error can be categorized as systematic and non-systematic error. In this paper, we suggest a novel method to calibrate systematic error using inherent home positioning capability of home cleaning robot. The method is designed for a differential drive type and take advantage of Augmented extended Kalman Fil- ter(AKF) Algorithm to estimates systematic error parameters. Our approach has both characteristics of on-line and off-line. By simulation and experiment, we evaluate the method and the result shows that the proposed method gives odometry error reduction by several times.
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