9 citations · 10 across the 5 of their papers we have counts for
5 papers
GAP-RL: Grasps As Points for RL Towards Dynamic Object Grasping
Pengwei Xie, Siang Chen, Qianrun Chen +5
Dynamic grasping of moving objects in complex, continuous motion scenarios remains challenging. Reinforcement Learning (RL) has been applied in various robotic manipulation tasks,…
Diffusion-Based Depth Inpainting for Transparent and Reflective Objects
Tianyu Sun, Dingchang Hu, Yixiang Dai +1
Transparent and reflective objects, which are common in our everyday lives, present a significant challenge to 3D imaging techniques due to their unique visual and optical properti…
Target-Oriented Object Grasping via Multimodal Human Guidance
Pengwei Xie, Siang Chen, Dingchang Hu +3
In the context of human-robot interaction and collaboration scenarios, robotic grasping still encounters numerous challenges. Traditional grasp detection methods generally analyze…
Region-aware Grasp Framework with Normalized Grasp Space for Efficient 6-DoF Grasping
Siang Chen, Pengwei Xie, Wei Tang +3
A series of region-based methods succeed in extracting regional features and enhancing grasp detection quality. However, faced with a cluttered scene with potential collision, the…
Rethinking 6-Dof Grasp Detection: A Flexible Framework for High-Quality Grasping
Pengwei Xie, Siang Chen, Wei Tang +3
Robotic grasping is a primitive skill for complex tasks and is fundamental to intelligence. For general 6-Dof grasping, most previous methods directly extract scene-level semantic…