轮式机器人控制回路中的人工神经网络

2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE) Pub Date : 2021-03-11 DOI:10.1109/REEPE51337.2021.9388047

O. Glukhov, N. Masalkova, R. Kulikov, T. Brovko, D. Tsaregorodtsev

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引用次数: 1

摘要

本文描述了一个跟踪系统的创建，该系统由一个轮式机器人跟踪一个目标(例如，一个人)。机器人的控制回路采用人工神经网络(ANN)来确定目标的距离和方位，即跟踪参数。这项工作的主要重点是开发一个能够计算跟踪参数的近最优估计的人工神经网络的计算机模型。在这种情况下，使用跟踪参数估计的均方根误差(RMSE)作为人工神经网络运行效率的标准。结果，对于最佳的人工神经网络模型，范围的RMSE为0.009 m，轴承为1.006度。

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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Artificial Neural Network in the Control Loop of a Wheeled Robot

This paper describes the creation of a tracking system represented by a wheeled robot following a target (for example, a human). An artificial neural network (ANN) is used in the control loop of the robot to determine the range and bearing of the target, which are the tracking parameters. The main focus of the work is to develop a computer model of ANN capable of calculating near-optimal estimates of tracking parameters. In this case, the root mean square error (RMSE) of tracking parameter estimates is used as the criterion of efficiency of ANN operation. As a result, for the best ANN model the RMSE for the range was 0.009 m, and for the bearing was 1.006 degrees.

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2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

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