Human activities are hugely restricted by COVID-19, recently. Robots that can conduct inter-floor navigation attract much public attention, since they can substitute human workers to conduct the service work. However, current robots either depend on human assistance or elevator retrofitting, and fully autonomous inter-floor navigation is still not available. As the very first step of inter-floor navigation, elevator button segmentation and recognition hold an important position. Therefore, we release the first large-scale publicly available elevator panel dataset in this work, containing 3,718 panel images with 35,100 button labels, to facilitate more powerful algorithms on autonomous elevator operation. Together with the dataset, a number of deep learning based implementations for button segmentation and recognition are also released to benchmark future methods in the community. The dataset will be available at \url{https://github.com/zhudelong/elevator_button_recognition

翻译：人类活动最近受到COVID-19(COVID-19)的极大限制。 能够进行楼层间导航的机器人吸引了公众的极大关注,因为他们可以替代人类工人从事服务工作。 但是,目前的机器人要么依靠人手援助,要么依靠电梯改装,完全自主的楼层间导航仍然无法提供。 作为楼层间导航、电梯按钮分割和识别的第一步,这个工作的第一个重要位置。 因此,我们发布了这项工作中第一套大规模公开提供的电梯板数据集,其中包括3,718个配有35,100个按钮标签的面板图像,以便利在自动电梯操作中使用更强大的算法。 与数据集一起,一些基于深层学习的按钮分割和识别功能也发布在社区中,以作为今后方法的基准。 数据集将在以下提供:https://github.com/zudelong/elevator_button_sation_cogation)。