ISMR 2024 Workshop: Machine Learning with the da Vinci Research Kit
Workshop Date: Monday, June 3, 2024, 8:30-12:00 (half-day)
Venue: Georgia Institute of Technology, Atlanta, GA USA
Location: Marcus 1117
Objectives
The objective of this workshop is to advance the application of machine learning in robotic surgery. The primary application domain is the telesurgical approach exemplified in operating rooms by the da Vinci surgical system and in research labs by the da Vinci Research Kit (dVRK) and Raven II open platforms.
This workshop will consist of invited research presentations and include a live demonstration. The primary focus will be on machine learning with the da Vinci, dVRK or Raven II, but relevant research performed with other platforms is welcome. All presentations will be in-person.
Organizers
| Peter Kazanzides, Adnan Munawar | Loris Fichera |
| Johns Hopkins University | Worcester Polytechnic Institute |
| Jie Ying Wu | Zonghe Chua |
| Vanderbilt University | Case Western Reserve |
Final Program
Session 1: Invited Talks and Demonstration (90 minutes)
| Time | Title | Speakers |
|---|---|---|
| 8:30 | Machine Learning with the da Vinci Research Kit | Peter Kazanzides, JHU |
| 8:45 | Live demonstration | Juan Barragan, Haoying (Jack) Zhou, JHU/WPI |
| 9:15 | Perception Complementarity in Robot Assisted Surgeries | Yun-Hsuan (Melody) Su, Mt. Holyoke |
| 9:30 | Augmented Dexterity: Toward Surgical Subtask Autonomy under Surgeon Supervision | Kush Hari, UC Berkeley |
| 9:45 | Data and AI/ML in robotic surgery: Translation to clinical environments | Tony Jarc, Intuitive Surgical |
Coffee Break: (30 minutes)
Session 2: Invited Talks (90 minutes)
| Time | Title | Speakers |
|---|---|---|
| 10:30 | From Blood and Guts to Bits and Bytes: Increasing Autonomy in Robotic Laser Surgery | Loris Fichera, WPI |
| 10:45 | Solving Challenges of Force Estimation in Deformable Environments through Less Real World Data and Labels | Zonghe Chua, Case Western Reserve |
| 11:00 | Bringing Machine Learning to the Core of Surgical Scene Reconstruction and Tracking | Shan Lin, UC San Diego |
| 11:15 | Learning Deformable Tissue Manipulation from Large-Scale Simulation and Small-Scale Demonstrations | Alan Kuntz, Univ. of Utah |
| 11:30 | Increasing autonomy in robotic surgery for tissue manipulation and resection | Pietro Valdastri, Univ. of Leeds |
| 11:45 | Machine Learning for Assessing Surgical Skill and Enhancing User Performance on the dVRK | Ann Majewicz Fey, Univ. of Texas, Austin |