基于MCL的移动机器人导航定位实验与分析

Tae Gyun Kim, N. Ko, Kwang-Jin Kim
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引用次数: 3

摘要

本文介绍了移动机器人蒙特卡罗定位方法的一些实验研究。该方法利用超声距离数据进行定位。超声波信号是由一个信标产生和辐射的,信标的位置是先验给定的。安装在机器人上的接收器利用接收到的超声波信号检测信标的距离。研究提出了一种基于传感器输出统计分析的距离传感传感器模型。在实验中,使用了商业化的信标和探测器。通过实验,验证了该方法在各种条件下的性能。实验证明了该方法在绑架情况下的有效性。特别是,分析了可用信标的数量如何影响定位性能。研究了静止机器人和运动机器人的定位性能。给出了机器人车轮在地面滑动情况下的定位性能。通过实验和分析,证明了该方法在绑架、车轮打滑以及可能只有两个传感器数据的情况下是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experiments and Analysis of MCL Based Localization for Mobile Robot Navigation
This paper describes some experimental study on Monte Carlo Localization (MCL) approach of a mobile robot. The proposed method uses ultrasonic range data for localization. Ultrasonic signal is generated and radiated from a beacon whose location is given a priori. The receiver located on board a robot detects the range from the beacon using the received ultrasonic signal. The research proposes a sensor model for the range sensing based on statistical analysis of the sensor output. In the experiments, commercialized beacons and detectors are used. Through the experiments, the performance of the proposed method is verified and compared under various conditions. The experiments show the performance of the method in case of kidnapping. Especially, analysis on how the number of available beacons affects the localization performance is provided. The localization performance is investigated for the case of stationary robot and moving robot. Also, it presents the localization performance in the case where the wheels of the robot slip on the floor. Through the experiments and analysis, it is demonstrated that the method works in the cases of kidnapping, wheel slip, and possibly with only two sensor data available.
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