We aim to combine the power of algorithmic approaches with the intuition and experience of human supervisors by giving users the ability to easily control and modify task scheduling formulations.
Published in Proceedings of the 31st IEEE International Conference on Robot & Human Interactive Communication, 2022
We present a bilevel optimization framework to enable a robot to perform task segmentation-based part selection, kit arrangement, and delivery scheduling to provide custom-tailored kits just in time—i.e., right when they are needed.
Published in Human-Robot Interaction: Workshop on Robots for Learning, 2021
We propose a classroom-based social robot tutoring system that targets reading comprehension skills, using methods inspired by successful embodied reading pedagogical practices.
