Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore.
Department of Electrical Engineering, University of Western Ontario, London, ON N6A 3K7, Canada.
Sensors (Basel). 2020 Jun 23;20(12):3543. doi: 10.3390/s20123543.
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.
移动机器人在清洁和卫生方面的作用在全球范围内日益增加。消毒和卫生是任何安全室内环境的两个组成部分，而这些因素在类似 COVID-19 的大流行情况下变得更加关键。门把手是高度敏感的接触点，容易受到污染。门把手清洁任务的自动化不仅对确保安全很重要，而且对提高效率也很重要。这项工作提出了一个通过人类支持机器人（HSR）实现清洁任务自动化的人工智能框架。整个清洁过程涉及移动底座运动、门把手检测以及 HSR 机械臂的控制，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。喷涂和擦拭之间的协作控制在机器人操作系统中开发。控制模块使用从检测模块获得的信息，为机器人生成任务/操作空间，并评估所需位置以驱动机械臂。通过数值模拟和在丰田 HSR 平台上的实验验证了完整的策略。
