Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation

no code implementations • 23 Feb 2025 • Yunhai Feng, Jiaming Han, Zhuoran Yang, Xiangyu Yue, Sergey Levine, Jianlan Luo

Solving complex long-horizon robotic manipulation problems requires sophisticated high-level planning capabilities, the ability to reason about the physical world, and reactively choose appropriate motor skills.

Finetuning Offline World Models in the Real World

no code implementations • 24 Oct 2023 • Yunhai Feng, Nicklas Hansen, Ziyan Xiong, Chandramouli Rajagopalan, Xiaolong Wang

In this work, we seek to get the best of both worlds: we consider the problem of pretraining a world model with offline data collected on a real robot, and then finetuning the model on online data collected by planning with the learned model.

Offline RL Reinforcement Learning (RL)

Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods

no code implementations • 7 Aug 2023 • Ya Jing, Xuelin Zhu, Xingbin Liu, Qie Sima, Taozheng Yang, Yunhai Feng, Tao Kong

However, the recipes of visual pre-training for robot manipulation tasks are yet to be built.

Contrastive Learning Robot Manipulation +1

SAM-RL: Sensing-Aware Model-Based Reinforcement Learning via Differentiable Physics-Based Simulation and Rendering

no code implementations • 27 Oct 2022 • Jun Lv, Yunhai Feng, Cheng Zhang, Shuang Zhao, Lin Shao, Cewu Lu

Model-based reinforcement learning (MBRL) is recognized with the potential to be significantly more sample-efficient than model-free RL.

Deformable Object Manipulation Model-based Reinforcement Learning +3