基于人工神经网络的机器人数据分类

Radhakrishnan Gopalapillai, J. Vidhya, Deepa Gupta, Sudarshan TSB
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引用次数: 7

摘要

由于时间序列数据在科学和商业领域中很常见,时间序列数据分析在这些领域中从可用数据中提取信息具有重要作用。本文介绍了应用人工神经网络(ANN)对机器人在模拟环境中导航的传感器收集的大量时间序列数据进行分析的方法。采用反向传播学习算法的人工神经网络系统利用传感器采集的数据对机器人遇到的不同场景进行分类。
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Classification of robotic data using artificial neural network
As time series data are common in the field of science and commerce, time series data analysis has an important role in these areas for extracting information from available data. This paper presents the application of Artificial Neural Networks (ANN) for analyzing huge amount of time series data collected by sensors mounted on a robot navigating in a simulated environment. The Artificial Neural Network system employing back propagation learning algorithm classified different scenarios encountered by the robot using the data collected by sensors.
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