3 citations · 3 across the 4 of their papers we have counts for
5 papers
PILOT: Guiding Long-Horizon World-Model Planning for Robot Manipulation with Visual Subgoals and Policy Priors
Yang Liu, Hanchen Cui, Karthik Desingh
Latent world-model planning has shown promising results in goal-conditioned robotic manipulation, but remains challenging for long-horizon planning due to limited temporal guidance…
Active Real-World Factor-Based Evaluation for Generalist Robot Policies
Andrew Liao, Hanchen Cui, Karthik Desingh +1
Generalist robot manipulation policies trained on large, diverse datasets have shown remarkable promise across a wide range of tasks. However, rigorously evaluating these policies…
DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning
Hanchen Cui, Sergio Arnaud, Arjun Majumdar +5
Pretrained vision-language-action (VLA) policies show promising zero-shot generalization, but often fail under deployment-time distribution shift, leading to decreased robustness a…
Fine-Tuning Hard-to-Simulate Objectives for Quadruped Locomotion: A Case Study on Total Power Saving
Ruiqian Nai, Jiacheng You, Liu Cao +4
Legged locomotion is not just about mobility; it also encompasses crucial objectives such as energy efficiency, safety, and user experience, which are vital for real-world applicat…
A Universal Semantic-Geometric Representation for Robotic Manipulation
Tong Zhang, Yingdong Hu, Hanchen Cui +2
Robots rely heavily on sensors, especially RGB and depth cameras, to perceive and interact with the world. RGB cameras record 2D images with rich semantic information while missing…