
Towards the New Generation of Smart Home-Care with Cloud-Based Internet of Humans and Robotic Things
Dandan Zhang; Jin Zheng

The burgeoning demand for home-care services, driven by a rapidly aging global population, necessitates innovative solutions to alleviate the burden on caregivers and enhance care quality. This paper introduces the development of an Internet of Human and Robotic Things (IoHRT) framework, which synergizes cloud computing and the Internet of Robotic Things (IoRT) with human-robot collaborative control mechanisms for home-care applications. The IoHRT framework is designed to enable the seamless integration of customizable robotic platforms with modular, scalable, and compatible features, thereby creating a dynamic and adaptable home-care ecosystem. By leveraging the scalability and computational power of cloud computing, the framework facilitates real-time data analysis and remote monitoring, thus enhancing the efficiency and effectiveness of home-care. We present an in-depth analysis of the key characteristics of IoHRT, supported by evidence embedded in our design, and conduct user studies to evaluate the framework from users' perspectives. We demonstrate the performance and utility of our proposed framework for the future of home-care applications.
Robot Learning for Service Robots
Learning from Demonstration for Automatic Tea Preparation for Service Robots
AARON ASAMOAH; Virginia Ruiz Garate; Dandan Zhang