Generalizable Articulation Modeling and Manipulation for Articulated Objects
The author proposes the GAMMA framework to model articulation parameters and grasp pose affordance from point clouds, enhancing manipulation performance through adaptive learning.
GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects
提案されたGAMMAフレームワークは、点群から関節パラメータとグラスポーズアフォーダンスを推定し、実際の軌跡を利用して関節パラメータを反復的に更新して操作性能を向上させます。
CenterArt: Simultaneous 3D Shape Reconstruction and 6-DoF Grasp Estimation for Articulated Objects
CenterArt is a novel approach for simultaneous 3D shape reconstruction and 6-DoF grasp estimation of articulated objects from RGB-D images.
FlowBot++: Learning to Manipulate Generalized Articulated Objects via Articulation Projection
FlowBot++ is a deep 3D vision-based robotic system that predicts dense per-point motion (Articulation Flow) and dense per-point articulation parameters (Articulation Projection) to enable generalized manipulation of articulated objects.
Precise Articulated Object Manipulation through Online Axis Estimation and SAM2-Based Tracking
Our closed-loop pipeline integrates interactive perception with online refined axis estimation, enabling adaptive and precise control during manipulation tasks involving articulated objects.
