1 citations · 1 across the 3 of their papers we have counts for
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VidAct: Learning Manipulation from In-the-Wild Videos with Object-Centric 3D Awareness
Hang Li, Mingxin Zhang, Zihan Wu +9
Video demonstrations offer a scalable alternative to costly robot data for learning manipulation, yet existing reconstruction-based approaches often rely on constrained camera view…
ReMem-VLA: Empowering Vision-Language-Action Model with Memory via Dual-Level Recurrent Queries
Hang Li, Fengyi Shen, Dong Chen +6
Vision-language-action (VLA) models for closed-loop robot control are typically cast under the Markov assumption, making them prone to errors on tasks requiring historical context.…
DexGANGrasp: Dexterous Generative Adversarial Grasping Synthesis for Task-Oriented Manipulation
Qian Feng, David S. Martinez Lema, Mohammadhossein Malmir +4
We introduce DexGanGrasp, a dexterous grasping synthesis method that generates and evaluates grasps with single view in real time. DexGanGrasp comprises a Conditional Generative Ad…
Language-Guided Object-Centric Diffusion Policy for Generalizable and Collision-Aware Robotic Manipulation
Hang Li, Qian Feng, Zhi Zheng +3
Learning from demonstrations faces challenges in generalizing beyond the training data and often lacks collision awareness. This paper introduces Lan-o3dp, a language-guided object…
Evaluating Uncertainty-based Failure Detection for Closed-Loop LLM Planners
Zhi Zheng, Qian Feng, Hang Li +2
Recently, Large Language Models (LLMs) have witnessed remarkable performance as zero-shot task planners for robotic manipulation tasks. However, the open-loop nature of previous wo…