7 papers
Robotic Grasping and Placement Controlled by EEG-Based Hybrid Visual and Motor Imagery
Yichang Liu, Tianyu Wang, Ziyi Ye +4
We present a framework that integrates EEG-based visual and motor imagery (VI/MI) with robotic control to enable real-time, intention-driven grasping and placement. Motivated by th…
Sequential Multi-Object Grasping with One Dexterous Hand
Sicheng He, Zeyu Shangguan, Kuanning Wang +4
Sequentially grasping multiple objects with multi-fingered hands is common in daily life, where humans can fully leverage the dexterity of their hands to enclose multiple objects.…
RAG-6DPose: Retrieval-Augmented 6D Pose Estimation via Leveraging CAD as Knowledge Base
Kuanning Wang, Yuqian Fu, Tianyu Wang +4
Accurate 6D pose estimation is key for robotic manipulation, enabling precise object localization for tasks like grasping. We present RAG-6DPose, a retrieval-augmented approach tha…
You Only Estimate Once: Unified, One-stage, Real-Time Category-level Articulated Object 6D Pose Estimation for Robotic Grasping
Jingshun Huang, Haitao Lin, Tianyu Wang +3
This paper addresses the problem of category-level pose estimation for articulated objects in robotic manipulation tasks. Recent works have shown promising results in estimating pa…
CAP-Net: A Unified Network for 6D Pose and Size Estimation of Categorical Articulated Parts from a Single RGB-D Image
Jingshun Huang, Haitao Lin, Tianyu Wang +3
This paper tackles category-level pose estimation of articulated objects in robotic manipulation tasks and introduces a new benchmark dataset. While recent methods estimate part po…
HOP: Heterogeneous Topology-based Multimodal Entanglement for Co-Speech Gesture Generation
Hongye Cheng, Tianyu Wang, Guangsi Shi +2
Co-speech gestures are crucial non-verbal cues that enhance speech clarity and expressiveness in human communication, which have attracted increasing attention in multimodal resear…