6 papers
ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations
Yiwen Liu, Yujun Zhu, Kui Jia +3
Recent vision-based action models have demonstrated strong capabilities in complex manipulation, but they rarely leverage explicit object physical properties to adapt their policie…
Pose-Agnostic Robotic Functional Grasping via Observation-Action Canonicalization
Le Qiu, Cole Harrison, Jiankai Sun +5
Functional robotic grasping requires a policy that generalizes across diverse object geometries and poses while maintaining task-specific contact precision. We study this challenge…
FPC-VLA: A Vision-Language-Action Framework with a Supervisor for Failure Prediction and Correction
Yifan Yang, Zhixiang Duan, Tianshi Xie +8
Robotic manipulation is a fundamental component of automation. However, traditional perception-planning pipelines often fall short in open-ended tasks due to limited flexibility, w…
TacRefineNet: Goal-Conditioned Tactile Grasp Refinement for Edge-Prominent Objects
Shuaijun Wang, Haoran Zhou, Diyun Xiang +1
Accurate final grasp alignment remains challenging for edge-prominent objects such as thin plates, discs, and rods, whose sparse contacts are easily occluded and poorly resolved by…
DyDexHandover: Human-like Bimanual Dynamic Dexterous Handover using RGB-only Perception
Haoran Zhou, Yangwei You, Shuaijun Wang
Dynamic in air handover is a fundamental challenge for dual-arm robots, requiring accurate perception, precise coordination, and natural motion. Prior methods often rely on dynamic…
Dual-Actor Fine-Tuning of VLA Models: A Talk-and-Tweak Human-in-the-Loop Approach
Piaopiao Jin, Qi Wang, Guokang Sun +3
Vision-language-action (VLA) models demonstrate strong generalization in robotic manipulation but face challenges in complex, real-world tasks. While supervised fine-tuning with de…