Development of control algorithm for autonomous intelligent robotic complex (AIRTC)

Igor Kozulin, Andrey Chernyavskiy, Alexander Nazarov
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Abstract

The work is dedicated to the development of a control algorithm for the autonomous intelligent robotic complex (AIRTC). The unmanned ground vehicle consists of a corpus that contains batteries, motor wheels, sensors, video cameras, on-board computer for processing data from sensors and video cameras. The general dimensions of the autonomous mobile robotic platform are 780x650x550 mm. The small size of the mobile platform allows it to be used in small areas, where the use of other vehicles is economically unprofitable. The key role in the autonomous mode of operation of the robotic complex is intended to the use of machine learning technologies to realize the possibility of performing the task assigned to the autonomous robotic platform in indoor and outdoor areas. An algorithm has been developed to control the basic platform of an autonomous robotic technical complex and to detect key obstacles automatically using a neural network. The accuracy of detecting the eight designated classes of obstacles was 85%.
开发自主智能机器人综合体(AIRTC)的控制算法
这项工作致力于开发自主智能机器人综合体(AIRTC)的控制算法。无人地面车辆由一个包含电池、电机轮、传感器、摄像机、处理传感器和摄像机数据的机载计算机的主体组成。自主移动机器人平台的总体尺寸为 780x650x550 毫米。移动平台的小尺寸使其可以在小区域内使用,而在这些区域内使用其他车辆在经济上是不划算的。在机器人综合体的自主运行模式中起关键作用的是机器学习技术的使用,以实现在室内和室外区域执行分配给自主机器人平台的任务的可能性。已开发出一种算法,用于控制自主机器人技术综合体的基本平台,并利用神经网络自动检测关键障碍物。对指定的八类障碍物的检测准确率为 85%。
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