A Simple Algorithm for Person-Following Robot Control with Differential Wheeled based on Depth Camera

2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE) Pub Date : 2019-10-01 DOI:10.1109/ICOMITEE.2019.8921165

S. Kautsar, B. Widiawan, B. Etikasari, Saiful Anwar, Rosiana Dwi Yunita, M. Syai’in

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引用次数: 3

Abstract

Industrial Revolution 4.0 is the center of automatic technology development and adoption. This applies to the development of industrial automation and information technology. In the manufacturing industry, machines have been able to work autonomously to carry out the production process quickly and precisely. Even in the development of information technology, expert systems have been embedded in various smart phones. There are many things that can be controlled through smart phones that are connected to the internet network. Not only in manufacturing industries or offices, the development of industrial technology 4.0 has also begun to be implemented in homes. Automatic robotic cleaning technology, or smart home applications can be used commercially. In fact, using people tracking technology, automatic trolleys have been applied to help consumers in supermarkets. In this paper, person-following robot was developed. We use depth cameras to recognize human movement. 3D data is used as a reference value in a human follower system. Minimizing computing time, the dynamic decision tree method is used. This offers lighter and faster computational processing than using the fuzzy or NN method. Based on the testing result, a good robot performance is obtained. Robots can follow human movements in real-time on various testing paths.

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基于深度相机的差动轮式人跟随机器人简单控制算法

工业革命4.0是自动化技术开发和采用的中心。这适用于工业自动化和信息技术的发展。在制造业中，机器已经能够自主工作，快速而精确地执行生产过程。即使在信息技术的发展中，专家系统也已经嵌入到各种智能手机中。有很多东西可以通过连接到互联网的智能手机来控制。不仅在制造业或办公室，工业技术4.0的发展也开始在家庭中实施。自动机器人清洁技术，或者智能家居应用都可以商业化使用。事实上，利用人的跟踪技术，自动手推车已经被应用于帮助超市的消费者。本文研制了人跟随机器人。我们用深度相机来识别人体运动。在人体跟随系统中，三维数据被用作参考值。采用动态决策树方法，最大限度地减少计算时间。这提供了比使用模糊或神经网络方法更轻和更快的计算处理。根据测试结果，获得了良好的机器人性能。机器人可以在各种测试路径上实时跟踪人类的运动。

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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来源期刊

2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE)

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