Occupancy Network-Guided Autonomous Robotic Partial Nephrectomy
Autonomous soft-tissue cancer surgery has been limited to interventions on organ surfaces, because current systems cannot perceive and adapt to anatomy once it deforms or is cut. We introduce the first vision-guided autonomous system capable of performing complete tumor resections for partial nephrectomy. Our system integrates conditional occupancy networks, trained entirely in a physics-based simulation, that infer full 3-D anatomy (tumor, margin tissue, and kidney) from single-view partial point clouds. These occupancy networks maintain intraoperative tracking even as tissue is cut and deformed, enabling adaptive planning and execution. The surgical platform combines a depth camera for ...
| Authors | Ethan Kilmer, Pit Henrich, Jiawei Ge et al. |
|---|---|
| Primary category | cs.RO |
| Published | 14 September 2026 |
| Last updated at source | 14 September 2026 |
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