23 citations · 49 across the 11 of their papers we have counts for
7 papers · 1 filter
MISTac: A Vision-Based Tactile Sensor for Minimally Invasive Surgery
Robin Koch, Annabella Mascot, Rayan Younis +5
Minimally invasive and robot-assisted surgery offer many advantages over traditional open surgery, but deprive surgeons of tactile feedback and the ability to palpate tissue with t…
Point Cloud Segmentation for Autonomous Clip Positioning in Laparoscopic Cholecystectomy on a Phantom
Balázs Gyenes, Nikolai Franke, Paul Maria Scheikl +5
High-risk applications in robotics, such as robot-assisted surgery, present unique challenges. These systems must be both highly precise and interpretable in order to be deployed i…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
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…
The Dresden Dataset for 4D Reconstruction of Non-Rigid Abdominal Surgical Scenes
Reuben Docea, Rayan Younis, Yonghao Long +10
The D4D Dataset provides paired endoscopic video and high-quality structured-light geometry for evaluating 3D reconstruction of deforming abdominal soft tissue in realistic surgica…
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…