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LAMP: Lift Image-Editing as General 3D Priors for Open-world Manipulation
Jingjing Wang, Zhengdong Hong, Chong Bao +3
Human-like generalization in open-world remains a fundamental challenge for robotic manipulation. Existing learning-based methods, including reinforcement learning, imitation learn…
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning
Huihan Liu, Changyeon Kim, Bo Liu +2
Continual learning is a long-standing challenge in robot policy learning, where a policy must acquire new skills over time without catastrophically forgetting previously learned on…
ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning
Yiting Chen, Kenneth Kimble, Edward H. Adelson +20
Dexterous manipulation enables robots to purposefully alter the physical world, transforming them from passive observers into active agents in unstructured environments. This capab…
RoboCasa365: A Large-Scale Simulation Framework for Training and Benchmarking Generalist Robots
Soroush Nasiriany, Sepehr Nasiriany, Abhiram Maddukuri +1
Recent advances in robot learning have accelerated progress toward generalist robots that can perform everyday tasks in human environments. Yet it remains difficult to gauge how cl…