11 papers
Lightweight Learning from Actuation-Space Demonstrations via Flow Matching for Whole-Body Soft Robotic Grasping
Liudi Yang, Yang Bai, Yuhao Wang +4
Robotic grasping under uncertainty remains a fundamental challenge due to its uncertain and contact-rich nature. Traditional rigid robotic hands, with limited degrees of freedom an…
VideoWeaver: Multimodal Multi-View Video-to-Video Transfer for Embodied Agents
George Eskandar, Fengyi Shen, Mohammad Altillawi +4
Recent progress in video-to-video (V2V) translation has enabled realistic resimulation of embodied AI demonstrations, a capability that allows pretrained robot policies to be trans…
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.…
ConfCtrl: Enabling Precise Camera Control in Video Diffusion via Confidence-Aware Interpolation
Liudi Yang, George Eskandar, Fengyi Shen +5
We address the challenge of novel view synthesis from only two input images under large viewpoint changes. Existing regression-based methods lack the capacity to reconstruct unseen…
CoVAR: Co-generation of Video and Action for Robotic Manipulation via Multi-Modal Diffusion
Liudi Yang, Yang Bai, George Eskandar +5
We present a method to generate video-action pairs that follow text instructions, starting from an initial image observation and the robot's joint states. Our approach automaticall…
DRAW2ACT: Turning Depth-Encoded Trajectories into Robotic Demonstration Videos
Yang Bai, Liudi Yang, George Eskandar +4
Video diffusion models provide powerful real-world simulators for embodied AI but remain limited in controllability for robotic manipulation. Recent works on trajectory-conditioned…