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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
TAIL-Safe: Task-Agnostic Safety Monitoring for Imitation Learning Policies
Riad Ahmed, Momotaz Begum
Recent imitation learning (IL) algorithms such as flow-matching and diffusion policies demonstrate remarkable performance in learning complex manipulation tasks. However, these pol…
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…