The installation of remotely-operated service robots in the environments of our daily life (including offices, homes, and hospitals) can improve work-from-home policies and enhance the quality of the so-called new normal. However, it is evident that remotely-operated robots must have partial autonomy and the capability to learn and use local semiotic knowledge. In this paper, we argue that the development of semiotically adaptive cognitive systems is key to the installation of service robotics technologies in our service environments. To achieve this goal, we describe three challenges: the learning of local knowledge, the acceleration of onsite and online learning, and the augmentation of human–robot interactions.

在我们日常生活环境（包括办公室、家庭和医院）中安装远程操作的服务机器人可以改善在家工作的政策，提高所谓新常态的质量。然而，很明显，远程操作的机器人必须具有部分自主权以及学习和使用本地符号学知识的能力。在本文中，我们认为符号自适应认知系统的发展是在我们的服务环境中安装服务机器人技术的关键。为了实现这一目标，我们描述了三个挑战：本地知识的学习、现场和在线学习的加速以及人机交互的增强。