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Found 5 papers, 1 papers with code
From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction
Surgical automation requires precise guidance and understanding of the scene.
LUDO: Low-Latency Understanding of Deformable Objects using Point Cloud Occupancy Functions
Accurately determining the shape of objects and the location of their internal structures within deformable objects is crucial for medical tasks that require precise targeting, such as robotic biopsies.
Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects
Policy learning in robot-assisted surgery (RAS) lacks data efficient and versatile methods that exhibit the desired motion quality for delicate surgical interventions.
Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud
In deformable object manipulation, we often want to interact with specific segments of an object that are only defined in non-deformed models of the object.
Grounding Graph Network Simulators using Physical Sensor Observations
Our method results in utilization of additional point cloud information to accurately predict stable simulations where existing Graph Network Simulators fail.
