# CHARMIE: A Collaborative Healthcare and Home Service and Assistant Robot for Elderly Care
###### Abstract
It targets the development of a novel framework to model mixed human-robot societies and its demonstration using a network of heterogeneous robots and sensors in an oncological hospital's pediatric area. It  
Figure 1: CHARMIE (Collaborative Healthcare/Home Assistant Robot by Minho Industrial Electronics) different variations. (**a**) Conceptual sketch of the anthropomorphic robot. (**b**) Developed anthropomorphic design. (**c**) Primary prototype assembled. can handle uncertainties introduced by people and robots, generate natural interactions and engage in educational entertainment activities. However, the previously mentioned robots only solve tasks using pre-programmed methods and cannot generalise to different task variations or significant environmental changes. Robotics competitions can be used for benchmarking specific functionalities and integrated systems [19,20]. RoboCup@Home [21,22] is no exception and is regarded as a top competition with numerous state-of-the-art contributions in the field of service and assistive robotics. The goal is to foster the development of versatile domestic service robots that operate safely in daily life non-standardised environments. Some of the robots achieving the best results in the latest competitions are Walking Machine [23], RoboFEI [24], CATIE [25], Homer [26] and AMIGO [27]. Recent years have shown robots solving a wide range of different domestic tasks, like watering plants, taking the trash out, storing groceries, serving breakfast, cleaning and setting up a table. These tasks provide broad coverage of multidisciplinary subjects such as Navigation, Mapping, Person Recognition, Person Tracking, Object Recognition, Object Manipulation, Speech Recognition, Gesture Recognition and Cognition. Even though the tasks referred fit the domestic environment standards, these can straightforwardly be adapted to healthcare purposes and environments due to their genericness. Regarding cognition, RoboCup@Home teams are already using machine learning technique primarily based on supervised learning to solve tasks such as face recognition [28], body pose estimation [29,30] and object detection [31,32]. The presented robot, CHARMIE, is an anthropomorphic general service and assistive robot that focuses on healthcare and domestic environments to aid elderly people and healthcare employees. The purpose of CHARMIE is to provide a robotic solution capable of providing healthcare support and more independent life, assisting both the elderly's cognitive and physical health. It can perform a wide range of tasks in almost all non-standardised indoor environments and some outdoor environments. The primary focus regarding environments are nursing homes, hospitals, healthcare facilities, and domestic houses. These show the highest necessity and opportunity to integrate a robotic system capable of helping elderly people and healthcare workers. The capability of a wide range of tasks allows this robot to help in various domains, such as pick and place tasks, goods transportation, following workers/patients/users, speech communication (hearing and talking), visual analysis of the environment, navigation, object recognition and manipulation. The cooperative and collaborative aspect is demonstrated by the robot's ability to perform tasks parallel to user chores and even aid in tasks that the user cannot perform alone. The generic tasks described can be easily adapted to the robot's purpose. An example of pick and place tasks adapted to the purpose and environment can be: (i) delivering food trays to patients in hospitals; (ii) collecting crutches from residents in nursing homes; (iii) transporting boxes of medicines between different areas in healthcare facilities; and (iv) setting and cleaning up a table or loading a washing machine at a house. The variety of different tasks these generic robots can perform allows the robot to help in various ways, whichever best suits the user's present needs.