5 papers
Supervised Mixture-of-Experts for Surgical Grasping and Retraction
Lorenzo Mazza, Ariel Rodriguez, Rayan Younis +6
Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due to data scarcity, constrained workspace…
An Open-Source Robotics Research Platform for Autonomous Laparoscopic Surgery
Ariel Rodriguez, Lorenzo Mazza, Martin Lelis +4
Autonomous robot-assisted surgery demands reliable, high-precision platforms that strictly adhere to the safety and kinematic constraints of minimally invasive procedures. Existing…
LAR-MoE: Latent-Aligned Routing for Mixture of Experts in Robotic Imitation Learning
Ariel Rodriguez, Chenpan Li, Lorenzo Mazza +5
Imitation learning enables robots to acquire manipulation skills from demonstrations, yet deploying a policy across tasks with heterogeneous dynamics remains challenging, as models…
Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections
Max Kirchner, Alexander C. Jenke, Sebastian Bodenstedt +5
Purpose: Data privacy regulations hinder the creation of generalizable foundation models (FMs) for surgery by preventing multi-institutional data aggregation. This study investigat…
XiCAD: Camera Activation Detection in the Da Vinci Xi User Interface
Alexander C. Jenke, Gregor Just, Claas de Boer +3
Purpose: Robot-assisted minimally invasive surgery relies on endoscopic video as the sole intraoperative visual feedback. The DaVinci Xi system overlays a graphical user interface…