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A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework

机译:使用深度学习框架清洁和维护门把手的人类支持机器人

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摘要

The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that are prone to be contamination. Automation of the door-handle cleaning task is not only important for ensuring safety, but also to improve efficiency. This work proposes an AI-enabled framework for automating cleaning tasks through a Human Support Robot (HSR). The overall cleaning process involves mobile base motion, door-handle detection, and control of the HSR manipulator for the completion of the cleaning tasks. The detection part exploits a deep-learning technique to classify the image space, and provides a set of coordinates for the robot. The cooperative control between the spraying and wiping is developed in the Robotic Operating System. The control module uses the information obtained from the detection module to generate a task/operational space for the robot, along with evaluating the desired position to actuate the manipulators. The complete strategy is validated through numerical simulations, and experiments on a Toyota HSR platform.
机译:在全球范围内,用于清洁和卫生目的的移动机器人的作用正在增加。消毒和卫生是任何安全室内环境的两个组成部分,在类似COVID-19的大流行情况下,这些因素变得越来越重要。门把手是高度敏感的接触点,容易被污染。门把手清洁任务的自动化不仅对于确保安全至关重要,而且对于提高效率也很重要。这项工作提出了一个支持AI的框架,用于通过人类支持机器人(HSR)自动执行清洁任务。整个清洁过程包括移动底座运动,门把手检测以及对HSR机械手的控制,以完成清洁任务。检测部分利用深度学习技术对图像空间进行分类,并为机器人提供一组坐标。在机器人操作系统中开发了喷涂和擦拭之间的协同控制。控制模块使用从检测模块获得的信息来为机器人生成任务/操作空间,并评估所需位置以致动机械手。通过数值模拟和在丰田HSR平台上进行的实验验证了完整的策略。

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