In the Autonomous Robot Training Lab at Olin College, I designed methods for offline policy stitching using the open-x embodiment dataset.

Specifically, I used Mujoco simulation environments to perform naive rollouts of tasks and cluster observations using k-means. Then, I utilized the centroids of those clusters as anchors to project new observations into a latent space interpretable to a second network. The second network mapped projected observations to robot actions.