Regular irradiation of indoor environments with ultraviolet C (UVC) light has become a regular task for many indoor settings as a result of COVID-19, but current robotic systems attempting to automate it suffer from high costs and inefficient irradiation. In this paper, we propose a purpose-made inexpensive robotic platform with off-the-shelf components and standard navigation software that, with a novel algorithm for finding optimal irradiation locations, addresses both shortcomings to offer affordable and efficient solutions for UVC irradiation. We demonstrate in simulations the efficacy of the algorithm and show a prototypical run of the autonomous integrated robotic system in an indoor environment. In our sample instances, our proposed algorithm reduces the time needed by roughly 30\% while it increases the coverage by a factor of 35\% (when compared to the best possible placement of a static light).
翻译:由于COVID-19,对室内环境定期进行紫外线C(UVC)光线辐照已成为许多室内环境的常规任务,但由于COVID-19,许多室内环境经常要定期进行这种辐照,但目前试图使室内环境自动化的机器人系统费用高昂,而且辐照效率低。 在本文中,我们提议建立一个有现成部件和标准导航软件的、有新颖算法的、有目的的廉价机器人平台,以寻找最佳辐照地点,解决为紫外线辐照提供负担得起和有效的解决办法的缺点。 我们在模拟算法的功效时展示了在室内环境中自动集成机器人系统的模拟运行。在我们的样本中,我们提议的算法减少了大约30个需要的时间,同时增加了35个系数(与静光的最佳位置相比 ) 。