5 citations · 5 across the 6 of their papers we have counts for
6 papers
Agentic RAG-VLM: Affordance-Aware Retrieval-Augmented Generation with Self-Reflective Planning for Robotic Grasping
Tao Chen, Lizheng Liu, Jiaxu Wang +4
Generalizable robotic grasping in cluttered environments is essential for deploying manipulators in unstructured human spaces, yet existing VLM-based methods rely on visual similar…
Combining Planning and Diffusion for Mobility with Unknown Dynamics
Yajvan Ravan, Zhutian Yang, Tao Chen +2
Manipulation of large objects over long horizons (such as carts in a warehouse) is an essential skill for deployable robotic systems. Large objects require mobile manipulation whic…
Vegetable Peeling: A Case Study in Constrained Dexterous Manipulation
Tao Chen, Eric Cousineau, Naveen Kuppuswamy +1
Recent studies have made significant progress in addressing dexterous manipulation problems, particularly in in-hand object reorientation. However, there are few existing works tha…
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
Zechu Li, Rickmer Krohn, Tao Chen +3
Deep reinforcement learning (RL) algorithms typically parameterize the policy as a deep network that outputs either a deterministic action or a stochastic one modeled as a Gaussian…
Learning Physical Dynamics for Object-centric Visual Prediction
Huilin Xu, Tao Chen, Feng Xu
The ability to model the underlying dynamics of visual scenes and reason about the future is central to human intelligence. Many attempts have been made to empower intelligent syst…
Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation
Marcel Torne, Anthony Simeonov, Zechu Li +4
Imitation learning methods need significant human supervision to learn policies robust to changes in object poses, physical disturbances, and visual distractors. Reinforcement lear…