Uploaded May 2018 | Updated September 2026, 2 weeks ago
ICRA 2018 Spotlight Video
Interactive Session Wed PM Pod A.4
Authors: Draelos, Mark; Keller, Brenton; Tang, Gao; Kuo, Anthony; Hauser, Kris; Izatt, Joseph
Title: Real-Time Image-Guided Cooperative Robotic Assist Device for Deep Anterior Lamellar Keratoplasty
Abstract:
Deep anterior lamellar keratoplasty (DALK) is a promising technique for corneal transplantation that avoids the chronic immunosuppression comorbidities and graft rejection risk associated with penetrating keratoplasty (PKP), the standard procedure. In DALK, surgeons must insert a needle 90% through the 500 um cornea without penetrating its underlying membrane. This pushes surgeons to their manipulation and visualization limits such that 59% of DALK attempts fail due to corneal perforation or inadequate needle depth. We propose a robot-assisted solution to jointly solve the manipulation and visualization challenges using a cooperatively-controlled, precise robot arm and live optical coherence tomography (OCT) imaging, respectively. Our system features an interface handle, with which the surgeon and robot cooperatively hold the tool, and a posterior corneal boundary virtual fixture driven by real-time OCT segmentation. A study in which three operators performed DALK needle insertions manually and cooperatively in ex vivo human corneas demonstrated an 84% improvement in perforation-free needle depth without an increased perforation rate.
ICRA 2018 Spotlight Video
Interactive Session Wed PM Pod A.4
Authors: Draelos, Mark; Keller, Brenton; Tang, Gao; Kuo, Anthony; Hauser, Kris; Izatt, Joseph
Title: Real-Time Image-Guided Cooperative Robotic Assist Device for Deep Anterior Lamellar Keratoplasty
Abstract:
Deep anterior lamellar keratoplasty (DALK) is a promising technique for corneal transplantation that avoids the chronic immunosuppression comorbidities and graft rejection risk associated with penetrating keratoplasty (PKP), the standard procedure. In DALK, surgeons must insert a needle 90% through the 500 um cornea without penetrating its underlying membrane. This pushes surgeons to their manipulation and visualization limits such that 59% of DALK attempts fail due to corneal perforation or inadequate needle depth. We propose a robot-assisted solution to jointly solve the manipulation and visualization challenges using a cooperatively-controlled, precise robot arm and live optical coherence tomography (OCT) imaging, respectively. Our system features an interface handle, with which the surgeon and robot cooperatively hold the tool, and a posterior corneal boundary virtual fixture driven by real-time OCT segmentation. A study in which three operators performed DALK needle insertions manually and cooperatively in ex vivo human corneas demonstrated an 84% improvement in perforation-free needle depth without an increased perforation rate.




![Real-Time CPU-Based Large-Scale 3D Mesh Reconstruction
ICRA 2018 Spotlight Video
Interactive Session Thu AM Pod R.1
Authors: Piazza, Enrico; Romanoni, Andrea; Matteucci, Matteo
Title: Real-Time CPU-Based Large-Scale 3D Mesh Reconstruction
Abstract:
In Robotics, especially in this era of autonomous driving, mapping is one key ability of a robot to be able to navigate through an environment, localize on it and analyze its traversability.To allow for real-time execution on constrained hardware, the map usually estimated by feature-based or semi-dense SLAM algorithms is a sparse point cloud; a richer and more complete representation of the environment is desirable. Existing dense mapping algorithms require extensive use of GPU computing and they hardly scale to large environments; incremental algorithms from sparse points still represent an effective solution when light computational effort is needed and big sequences have to be processed in real-time. In this paper we improved and extended the state of the art incremental manifold mesh algorithm proposed in [1] and extended in [2]. While these algorithms do not achieve real-time and they embed points from SLAM or Structure from Motion only when their position is fixed, in this paper we propose the first incremental algorithm able to reconstruct a manifold mesh in real-time through single core CPU processing which is also able to modify the mesh according to 3D points updates from the underlying SLAM algorithm. We tested our algorithm against two state of the art incremental mesh mapping systems on the KITTI dataset, and we showed that, while accuracy is comparable, our approach is able to reach real-time performances thanks to an order of magnitude speed-up. Real-Time CPU-Based Large-Scale 3D Mesh Reconstruction](https://i.ytimg.com/vi/VaLx6Klz13Y/mqdefault.jpg)





