We report on an exploratory study conducted at a graduate school in Sweden with a humanoid robot, Baxter. First, we describe a list of potentially useful capabilities for a robot teaching assistant derived from brainstorming and interviews with faculty members, teachers, and students. These capabilities consist of reading educational materials out loud, greeting, alerting, allowing remote operation, providing clarifications, and moving to carry out physical tasks. Secondly, we present feedback on how the robot’s capabilities, demonstrated in part with the Wizard of Oz approach, were perceived, and iteratively adapted over the course of several lectures, using the Engagement Profile tool. Thirdly, we discuss observations regarding the capabilities and the development process. Our findings suggest that using a social robot as a teaching assistant is promising using the chosen capabilities and Engagement Profile tool. We find that enhancing the robot’s autonomous capabilities and further investigating the role of embodiment are some important topics to be considered in future work.

In a case study, we transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphones or tablets with the option for further enhancement of the presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicated a positive impact of the program using a robot as compared to the program without a robot. In situ observations and interviews with day-care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously.

The papers in this special section focus on cyber-physical man-machine systems with particular emphasis on situation, activity, and goal awareness deployed in these systems. Recent advances in sensing technologies, the Internet of Things, pervasive computing, smart environments have transformed traditional embedded ICT systems into an ecosystem of interconnected and collaborating smart objects, devices, embedded systems, and most importantly humans. Such systems, often referred to as cyber-physical systems (CPS), are usually human user-driven or user-centered, and are aimed at providing people and businesses with a wide range of innovative applications and services. For example, a “smart home” can monitor and analyze the daily activities of its inhabitants, usually the elderly or individuals with disabilities, so that personalized context-aware assistance can be provided. A “smart city” can monitor, manage, and potentially control all basic city functionalities such as transport, energy supply, and waste collection, at a higher level of automation by collecting and harnessing sensor data across a large geographic expanse. In order to respond in real-time to an individual user’s specific needs in dynamic and complex situations, and to support ergonomics and user-friendliness through consideration of human factors such as privacy, dignity, and behavior characteristics, cyber-physical human–machine systems need to be aware of the physical environment and human participant behavior. This awareness enables effective and fast feedback loops between sensing and actuation, possibly with cognitive and learning capabilities adapting to participant preferences, capabilities, and the modality of human–machine interaction as well as dynamic situations.