papers
Publications (3)
cs.RO2025
Accelerated co-design of robots through morphological pretraining
Luke Strgar, Sam Kriegman
The co-design of robot morphology and neural control typically requires using reinforcement learning to approximate a unique control policy gradient for each body plan, demanding m…
cs.RO2024
Evolution and learning in differentiable robots
Luke Strgar, David Matthews, Tyler Hummer +1
The automatic design of robots has existed for 30 years but has been constricted by serial non-differentiable design evaluations, premature convergence to simple bodies or clumsy b…
eess.AS2022
Phoneme Segmentation Using Self-Supervised Speech Models
Luke Strgar, David Harwath
We apply transfer learning to the task of phoneme segmentation and demonstrate the utility of representations learned in self-supervised pre-training for the task. Our model extend…