Exploring the future of data-driven product design

Connected devices present new opportunities to advance design through data collection in the wild, similar to the way digital services evolve through analytics. However, it is still unclear how live data transmitted by connected devices informs the design of these products, going beyond performance optimisation to support creative practices. Design can be enriched by data captured by connected devices, from usage logs to environmental sensors, and data about the devices and people around them. Through a series of workshops, this paper contributes industry and academia perspectives on the future of data-driven product design. We highlight HCI challenges, issues and implications, including sensemaking and the generation of design insight. We further challenge current notions of data-driven design and envision ways in which future HCI research can develop ways to work with data in the design process in a connected, rich, human manner

Weed Robot

Team Weed Scouts has completed our work on a weed-cutting robot for the Girl Scouts of California’s Central Coast. The final robot build provides a solid foundation that can be built and improved upon by future teams. We have completed the robot base and structure, including the chassis, drivetrain, and robot shell. We also completed manufacturing a weed storage bin and canvas cover for the robot. Additionally, we have built a weed scooper, the mechanism that cuts weeds and transports them into a storage compartment. The electronics and programming for remote control of the robot are also implemented. After some testing, we found that the robot had limited functionality. It was able to drive around with slight power issues but unfortunately, the weed scooper was not able to fully cut and transport the weeds. Despite these obstacles, we have created a semi-operable foundation for future teams to optimize, test, and debug. The next steps include adding a weed shredder and developing autonomous robot functionality along with weed identification. Upon project completion, the weed-cutting robot will help maintain the grounds at Camp Arnaz and serve as a source of engineering inspiration for Girl Scouts and other camp visitors

Design for Children’s Playful Learning with Robots

This article presents an investigation of the implications of designing for children’s playful learning with robots. This study was carried out by adopting a Research through Design approach that resulted in the development of a novel low-anthropomorphic robot called Shybo. The article reports the main phases of the project: the preliminary and exploratory research that was carried out to define a list of design requirements; the design of the robot and its supplementary materials for carrying out playful learning experiences; and the evaluation of the project that involved both parents and children. The robot, in fact, was finally tested as part of a two-hour experience that engaged children in activities related to the associations between sounds and colours. The article presents and discusses the results of this evaluation to point out positive aspects of the experience, emerging issues and hints for future works. These are documented to share lessons learned that might be supportive of the general development of children’s playful learning and cognitive experiences with robots

Virgil Robot at Racconigi’s Castle: a Design Challenge.

This paper discusses the role of Design Research (DR) as a mediator between robotics and cultural heritage. This issue has been addressed in the project Virgil, a telepresence robot for visiting inaccessible areas of Racconigi Castle in Piedmont, Italy. A project developed applying an iterative design process that combines the traditional activities of design practice, such as product and service design, to a more theoretical and conceptual activities of DR aimed to generate a meaningful solution. Both the museum context and the state of the art of museum robotic applications have been analysed to define the ethical requirements for the development of the service. The analytical phase is followed by the design stage in which a service concept has been defined, through a process of continuous debate and co-design with various stakeholders. The process has led to the prototyping of a dedicated robot tested in the real environment with random visitors

Robotic Faces: Exploring Dynamical Patterns of Social Interaction between Humans and Robots

Thesis (Ph.D.) - Indiana University, Informatics, 2015The purpose of this dissertation is two-fold: 1) to develop an empirically-based design for an interactive robotic face, and 2) to understand how dynamical aspects of social interaction may be leveraged to design better interactive technologies and/or further our understanding of social cognition. Understanding the role that dynamics plays in social cognition is a challenging problem. This is particularly true in studying cognition via human-robot interaction, which entails both the natural social cognition of the human and the “artificial intelligence” of the robot. Clearly, humans who are interacting with other humans (or even other mammals such as dogs) are cognizant of the social nature of the interaction – their behavior in those cases differs from that when interacting with inanimate objects such as tools. Humans (and many other animals) have some awareness of “social”, some sense of other agents. However, it is not clear how or why. Social interaction patterns vary across culture, context, and individual characteristics of the human interactor. These factors are subsumed into the larger interaction system, influencing the unfolding of the system over time (i.e. the dynamics). The overarching question is whether we can figure out how to utilize factors that influence the dynamics of the social interaction in order to imbue our interactive technologies (robots, clinical AI, decision support systems, etc.) with some "awareness of social", and potentially create more natural interaction paradigms for those technologies. In this work, we explore the above questions across a range of studies, including lab-based experiments, field observations, and placing autonomous, interactive robotic faces in public spaces. We also discuss future work, how this research relates to making sense of what a robot "sees", creating data-driven models of robot social behavior, and development of robotic face personalities