3 papers
cs.RO2026
Spatio-Temporal Retrieval-based Priors for Adaptive Computational Teaching in Driving
Deepak Edakkattil Gopinath, Xiongyi Cui, Jonathan DeCastro +2
Learning-based automated coaching systems for complex motor tasks such as high-performance driving remain limited in the ability to be adaptive by their reliance only on local, con…
cs.RO2026
On the Strengths and Weaknesses of Data for Open-set Embodied Assistance
Pradyumna Tambwekar, Andrew Silva, Deepak Gopinath +3
Embodied foundation models are increasingly performant in real-world domains such as robotics or autonomous driving. These models are often deployed in interactive or assistive set…
cs.RO2024
Computational Teaching for Driving via Multi-Task Imitation Learning
Deepak Gopinath, Xiongyi Cui, Jonathan DeCastro +10
Learning motor skills for sports or performance driving is often done with professional instruction from expert human teachers, whose availability is limited. Our goal is to enable…