Search papers, labs, and topics across Lattice.
3
0
5
0
Achieving state-of-the-art performance in mobile manipulation hinges on aligning temporal granularity and action space, revealing critical insights into effective world-action modeling.
Ditch discrete waypoints: VLA models can now generate smooth, physically plausible robot trajectories by directly regressing continuous action functions.
By learning to project actions onto a low-dimensional manifold, ABot-M0 achieves faster and more stable robotic control policies compared to directly predicting actions in the full high-dimensional space.
