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David D. Yuan

2 accepted papers

2025

RoboCrowd: Scaling Robot Data Collection Through Crowdsourcing

ICRA 2025

In recent years, imitation learning from large-scale human demonstrations has emerged as a promising paradigm for training robot policies. However, the burden of collecting large quantities of human demonstrations is significant in terms of collection time and the need for access to expert operators

Cited by 9SourcecodeScholar
2025

Speedtuning: Speeding Up Policy Execution with Lightweight Reinforcement Learning

ICRA 2025

While learned robotic policies hold promise for advancing generalizable manipulation, their practical deployment is often hindered by suboptimal execution speeds. Imitation learning policies are inherently limited by hardware constraints and the speed of the operator during data collection. In addit

Cited by 2SourcecodeScholar