4 papers
Pre-training Visual Dexterity in Simulation
Sarthak Kamat, Adam Rashid, Satvik Sharma +4
Large-scale pre-training has made robot policy fine-tuning increasingly data-efficient, but this progress has largely been driven by datasets and embodiments built around simple pa…
SpeedTuning: Speeding Up Policy Execution with Lightweight Reinforcement Learning
David D. Yuan, Tony Z. Zhao, Kaylee Burns +1
While learned robotic policies hold promise for advancing generalizable manipulation, their practical deployment is often hindered by suboptimal execution speeds. Imitation learnin…
MemER: Scaling Up Memory for Robot Control via Experience Retrieval
Ajay Sridhar, Jennifer Pan, Satvik Sharma +1
Humans routinely rely on memory to perform tasks, yet most robot policies lack this capability; our goal is to endow robot policies with the same ability. Naively conditioning on l…
Ctrl-World: A Controllable Generative World Model for Robot Manipulation
Yanjiang Guo, Lucy Xiaoyang Shi, Jianyu Chen +1
Generalist robot policies can now perform a wide range of manipulation skills, but evaluating and improving their ability with unfamiliar objects and instructions remains a signifi…