To benefit from the social capabilities of a robot math tutor, instead of being distracted by them, a novel approach is needed where the math task and the robot's social behaviors are better intertwined. We present concrete design specifications of how children can practice math via a personal conversation with a social robot and how the robot can scaffold instructions. We evaluated the designs with a three-session experimental user study (n = 130, 8-11 y.o.). Participants got better at math over time when the robot scaffolded instructions. Furthermore, the robot felt more as a friend when it personalized the conversation.
MULTIFILE
Hospitalisation is stressful for children. Play material is often offered for distraction and comfort. Weexplored how contact with social robot PLEO could positively affect a child’s well-being. To this end, we performed a multiple case study on the paediatric ward of two hospitals. Child life specialists offered PLEO as a therapeutic activity to children in a personalised way for a well-being related purpose in three to five play like activity sessions during hospital visits/stay. Robot–child interaction was observed; care professionals, children and parents were interviewed. Applying direct content analysis revealed six categories of interest: interaction with PLEO, role of the adults, preferences for PLEO, PLEO as buddy, attainment of predetermined goal(s) and deployment of PLEO. Four girls and five boys, aged 4–13, had PLEO offered as a relief from stress or boredom or for physical stimulation. All but one started interacting with PLEO and showed behaviours like hugging, caring or technical exploration, promoting relaxation, activation and/or making contact. Interaction with PLEO contributed to achieving the well-being related purpose for six of them. PLEO was perceived as attractive to elicit play. Although data are limited, promising results emerge that the well-being of hospitalised children might be fostered by a personalised PLEO offer.
DOCUMENT
To benefit from the social capabilities of a robot math tutor, instead of being distracted by them, a novel approach is needed where the math task and the robot's social behaviors are better intertwined. We present concrete design specifications of how children can practice math via a personal conversation with a social robot and how the robot can scaffold instructions. We evaluated the designs with a three-session experimental user study (n = 130, 8-11 y.o.). Participants got better at math over time when the robot scaffolded instructions. Furthermore, the robot felt more as a friend when it personalized the conversation.
MULTIFILE
The CARTS (Collaborative Aerial Robotic Team for Safety and Security) project aims to improve autonomous firefighting operations through an collaborative drone system. The system combines a sensing drone optimized for patrolling and fire detection with an action drone equipped for fire suppression. While current urban safety operations rely on manually operated drones that face significant limitations in speed, accessibility, and coordination, CARTS addresses these challenges by creating a system that enhances operational efficiency through minimal human intervention, while building on previous research with the IFFS drone project. This feasibility study focuses on developing effective coordination between the sensing and action drones, implementing fire detection and localization algorithms, and establishing parameters for autonomous flight planning. Through this innovative collaborative drone approach, we aim to significantly improve both fire detection and suppression capabilities. A critical aspect of the project involves ensuring reliable and safe operation under various environmental conditions. This feasibility study aims to explore the potential of a sensing drone with detection capabilities while investigating coordination mechanisms between the sensing and action drones. We will examine autonomous flight planning approaches and test initial prototypes in controlled environments to assess technical feasibility and safety considerations. If successful, this exploratory work will provide valuable insights for future research into autonomous collaborative drone systems, currently focused on firefighting. This could lead to larger follow-up projects expanding the concept to other safety and security applications.
