Toddler Temperament Estimation from Robot Interaction Data
Through explainable machine learning (XAI), we analyze behavioral data from child-robot interactions to estimate toddlers’ temperament and personality. By clarifying in which …
Through explainable machine learning (XAI), we analyze behavioral data from child-robot interactions to estimate toddlers’ temperament and personality. By clarifying in which …
We study how the embodiment and dialogue design of robots can support communication between geographically separated people. From remote childcare robots that scaffold infant …
Intent signals from brain-machine interfaces (BMIs) are inherently low-bandwidth and noisy, making fine-grained robot control difficult. We build shared autonomy frameworks in …
We build frameworks that let autonomous robots explain their decision-making processes and the underlying reasoning to people in an understandable way. Through distributed …
We develop soft tactile sensors that enable rich bodily contact between robots and humans/environments. From multi-axis force sensors that combine magnetorheological elastomers …
Based on the framework of active inference, we propose an energy-minimization approach to multimodal affective human-robot interaction. The proposed mechanism enables a robot to …