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cs.RO2026
Contact-Anchored Policies: Contact Conditioning Creates Strong Robot Utility Models
Zichen Jeff Cui, Omar Rayyan, Haritheja Etukuru +16
The prevalent paradigm in robot learning attempts to generalize across environments, embodiments, and tasks with language prompts at runtime. A fundamental tension limits this appr…
cs.RO2024
PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement
Tewodros Ayalew, Xiao Zhang, Kevin Yuanbo Wu +3
We present PROGRESSOR, a novel framework that learns a task-agnostic reward function from videos, enabling policy training through goal-conditioned reinforcement learning (RL) with…