3 papers
cs.RO2026
Trajectory-Consistent Flow Matching for Robust Visuomotor Policy Learning
Riad Ahmed, Sujosh Nag, Moniruzzaman Akash +2
Flow matching policies learn continuous velocity fields that transport noise to actions, enabling fast deterministic inference for robot manipulation. However, standard training op…
cs.RO2026
A Principled Approach for Creating High-fidelity Synthetic Demonstrations for Imitation Learning
Moniruzzaman Akash, Momotaz Begum
Recent advances in 3D Gaussian Splatting (3DGS) have enabled visually realistic demonstration generation from a single expert trajectory and a short multi-view scan. However, exist…
cs.RO2026
To Do or Not to Do: Ensuring the Safety of Visuomotor Policies Learned from Demonstrations
Riad Ahmed, Moniruzzaman Akash, Momotaz Begum
Task success has historically been the primary measure of policy performance in imitation learning (IL) research. This characteristics strictly limits the ubiquitous applications o…