2 papers
cs.RO2026
RoboFFT: Finetuning generative robot policy via online reinforcement learning with forward process
Yu Li, Shenghe Hu, Yuhan Wang +4
Generative models, such as diffusion and flow-based models, have shown strong promise for robot policy learning by capturing complex and multimodal action distributions from demons…
cs.RO2026
Accelerating Robotic Reinforcement Learning with Agent Guidance
Haojun Chen, Zili Zou, Chengdong Ma +4
Reinforcement Learning (RL) offers a powerful paradigm for autonomous robots to master generalist manipulation skills through trial-and-error. However, its real-world application i…