Course Content
Orientation, introduction to the course
1. Human-Robot Interaction (HRI)
2. Research Methods in Human-Robot Interaction
3. Smart Cities & HRI
The demand for city living is already high, and it appears that this trend will continue. According to the United Nations World Cities Report, by 2050, more than 70% of the world's population will be living and working in cities — one of many reports predicting that cities will play an important role in our future (UN-Habitat, 2022). Thus, as cities are growing in size and scope, it is shaped into complex urban landscape where things, data, and people interact with each other. Everything and everyone has become so connected that Wifi too often fails to meet digital needs, online orders don't arrive fast enough, traffic jams still clog the roads and environmental pollution still weighs on cities. New technologies, technical intelligence, and robots can contribute to the direction of finding solutions to ever-increasing problems and assist the evolution of the growing urban space.
Human-Robot Interaction
About Lesson

Designing for Social Acceptability


We will talk about how a robot’s physical attributes can be used to increase social acceptance at both the user and observer levels in this section. From social interactions to food intake, physical appearance is crucial to many different aspects of daily life. Consumer opinion of physical appearance has a significant influence on perceived quality in every industry. As per Norman, “beautiful design helps people feel good” and this emotional state “by making it easier for people to discover solutions to the issues they meet” when using a product, facilitates problem-solving (Bartneck et al., 2004).


The form and function of a product, whether it be an appliance or a humanoid robot, affect how people perceive it, interact with it, and establish long-term relationships with it. Goetz et al. (2003) looked into how a robot’s conduct and outward appearance affected how well-liked it was by people. In their study, the writers mixed various appearances and behaviors before collecting responses from participants. Their research suggests that a robot’s appearance should match the work it does. Physical appearance also affects people’s attitudes toward robots. When a robot’s appearance is too human-like, it can be unsettling and cause the viewer to feel strange emotions like uneasiness or hostility.

Dario et al. (2001) was one of the early studies on the topic of personal robots that focuses on people’s perceptions of service robots, especially with regard to physical appearance. In this study it was assessed the acceptance of a modular mobile robotic system for personal assistance to disabled and elderly individuals at home using a realistic scenario in their study. Their research suggests that a human look is not required for personal robot design. Contrarily, striking the perfect balance between a home appliance’s and a machine’s appearance led to the best design solution.


In addition, in a public setting like urban areas, there can be ethical, social, and even legal implications for robots and their services that may arise. In conclusion, when it comes to service robots in public settings, there are three types of interactions that can occur: (1) interactions caused by the use of the robot (user interactions), (2) interactions that come about due to the robot’s presence among humans (bystander interactions), and (3) interactions that result from the robot being in its operating environment. These interactions could lead to negative reactions towards robots, such as resistance, at various levels. For instance, fear of the robot may cause social resistance among bystanders, a lack of legal regulations for robots could result in legal resistance, worries about job loss due to robots may result in resistance from workers, and ethical concerns about the use of robots for tasks such as caring for the elderly or disabled may generate ethical resistance (Salvini et al., 2010).


Bartneck, C., & Forlizzi, J. (2004, April). Shaping human-robot interaction: understanding the social aspects of intelligent robotic products. In CHI’04 Extended Abstracts on Human Factors in Computing Systems (pp. 1731-1732).

Goetz, J., Kiesler, S., & Powers, A. (2003, November). Matching robot appearance and behavior to tasks to improve human-robot cooperation. In The 12th IEEE International Workshop on Robot and Human Interactive Communication, 2003. Proceedings. ROMAN 2003. (pp. 55-60). Ieee.

Dario, P., Guglielmelli, E., & Laschi, C. (2001). Humanoids and personal robots: Design and experiments. Journal of robotic systems, 18(12), 673-690.

Salvini, P., Laschi, C., & Dario, P. (2010). Design for acceptability: improving robots’ coexistence in human society. International journal of social robotics, 2, 451-460.