Nowadays, the Fourth Industrial Revolution has brought artificial intelligence to the forefront, and more and more intelligent robots begin to be used in the hospitality industry. In this study, the application of service humanoid robots in the hospitality industry is investigated based on Cardiff Metropolitan University EUREKA Robotics Lab’s robot as reported by Lab (in Eureka robotics lab, 2017, https://www.cardiffmet.ac.uk/technologies/Pages/EUREKA-Robotics-Lab.aspx). The research ontology of this study is post-positivism. The research philosophy of this research is phenomenology. Phenomenological studies have indicated that this phenomenon can only be truly understood and experienced through subjective immersive research directly involving researchers, and the interaction among researchers is an integral part of the research. In this study, the data are collated through case researches and experimental interviews. Finally, Some proposals for transforming the traditional hospitality industry into the direction of intelligence is summarized. In future research, a technical model combining artificial intelligence will be further developed.

At present, industrial robotics focuses more on motion control and vision, whereas humanoid service robotics (HSRs) are increasingly being investigated and researched in the field of speech interaction. The problem and quality of human-robot interaction (HRI) has become a widely debated topic in academia. Especially when HSRs are applied in the hospitality industry, some researchers believe that the current HRI model is not well adapted to the complex social environment. HSRs generally lack the ability to accurately recognize human intentions and understand social scenarios. This study proposes a novel interactive framework suitable for HSRs. The proposed framework is grounded on the novel integration of Trevarthen’s (2001) companionship theory and neural image captioning (NIC) generation algorithm. By integrating image-to-natural interactivity generation and communicating with the environment to better interact with the stakeholder, thereby changing from interaction to a bionic-companionship. Compared to previous research a novel interactive system is developed based on the bionic-companionship framework. The humanoid service robot was integrated with the system to conduct preliminary tests. The results show that the interactive system based on the bionic-companionship framework can help the service humanoid robot to effectively respond to changes in the interactive environment, for example give different responses to the same character in different scenes.

With the rapid development of traditional industries, intelligent robots have been widely used in the hospitality industry. Although the development of intelligent robots faces a positive trend and a good market in the hospitality industry, it also faces the problem that robots cannot effectively collect and use user data in the field of human–computer interaction. It not only affects the interaction experience between users and robots, but also prevents companies from getting valuable feedback in a timely manner. In order for intelligent robots to effectively utilize interactive information, the user experience of robot entertainment is improved. This paper proposes and establishes a basic technical model called iRCXM. Combining the iRCXM model with a decision tree classification algorithm is excepted effectively improve the interaction experience between humans and robots in hospitality. This paper designs a model of intelligent robot based on decision tree algorithm. The model divides the user into three sections, each corresponding to a different standard function. Using a decision tree classification algorithm model is excepted effectively judge users’ current stage and whether they can move to the next stage. When the user reaches the final stage, it proves that the user has obtained a good interactive experience. At the same time, for users at different stages, the model will provide strategies for downward transformation so that companies can adjust and improve existing problems in a timely manner. In addition, the research developed a robot user interaction system based on the existing technology. The system is based on Android. Using HTTP protocol and Baidu Cloud AI API to realize simple face recognition and Sanbot-OpenSDK to implement simple robot control, the development of this system is to verify the feasibility of the model. The developed samples were tested in a real environment and feedback from customer experience was collected through semi-structured interviews. Finally, the feasibility of the model is verified.

Reliable communication is a critical factor for ensuring robust performance of multi-robot teams. A selection of results are presented here comparing the impact of poor network quality on team performance under several conditions. Two different processes for emulating degraded network signal strength are compared in a physical environment: modelled signal degradation (MSD), approximated according to increasing distance from a connected network node (i.e. robot), versus effective signal degradation (ESD). The results of both signal strength processes exhibit similar trends, demonstrating that ESD in a physical environment can be modelled relatively well using MSD.

Responding to these global COVID-19 changes for daily healthcare services clinic, while maintaining safe social distancing, the paper reports the humancentred iterative design with real-fields feasibility inquiries to investigate the first robotic nurse and her partners in Wales. The research adapted the ancient Eastern human nature of seven emotions and six biological wills for the selection criteria and novel design principles for the care robots. We report the preliminary work for integrating, customising, implementing and evaluating three novel robotic nurses: Robot Nightingale, Robot Almeida and Robot Eureka in a care home and a hospital. Bionic Scenarios Definition with 5 merging principles are extracted from the Feasibility Inquiries 1-3. Limitations are discussed from the stakeholders' experiences. Our research has no intension to replace human nurses, but a thoughtful feasibility and interdisciplinary study for bionic robotic nurses for conventional engineers' and practitioners' references.