Artur Banach

About

Artur Banach is a leading researcher in medical robotics, with a focus on enhancing the safety and precision of minimally invasive surgeries. His work spans computer vision, kinematic modeling, and autonomous robotic systems, particularly for orthopaedic and pulmonary interventions. Banach’s most cited paper, "Dense-ArthroSLAM" (2019, 47 citations), introduces a dense 3D reconstruction method for arthroscopy that robustly localizes cameras within narrow joint spaces, reducing the cognitive load on surgeons. He further advanced orthopaedic robotics with "Kinematic Model of the Human Leg Using DH Parameters" (2020, 17 citations), which provides accurate joint motion tracking for robotic-assisted procedures. His contributions to safety include "Active Constraints for Tool-Shaft Collision Avoidance" (2019, 16 citations), a system that prevents instrument collisions during teleoperated surgery. Banach’s recent work, "Conditional Autonomy in Robot-Assisted Transbronchial Interventions" (2025), explores semi-autonomous navigation for lung cancer staging, promising to improve outcomes in bronchoscopy. With over 90 total citations, Banach’s research is pivotal in making robotic surgery more intuitive, safer, and accessible, bridging the gap between human skill and machine precision.

Research Focus

Key Achievements

Top Papers

1. 1
   Dense-ArthroSLAM: Dense Intra-Articular 3-D Reconstruction With Robust Localization Prior for Arthroscopy

   47 citations · 2019
2. 2
   Kinematic Model of the Human Leg Using DH Parameters

   17 citations · 2020
3. 3
   Active Contraints for Tool-Shaft Collision Avoidance in Minimally Invasive Surgery

   16 citations · 2019
4. 4
   Anatomical Joint Measurement With Application to Medical Robotics

   8 citations · 2020
5. 5
   Conditional Autonomy in Robot-Assisted Transbronchial Interventions

   4 citations · 2025

Key Collaborators

Contact & Links