This document discusses the development of robotic systems for delivering cellular therapies to the retina. Age-related macular degeneration causes vision loss for 600,000 people in the UK alone. Manually delivering therapies is challenging due to constraints of the operating room and patient anatomy. Researchers are developing co-manipulated and single-arm flexible robotic systems to overcome these challenges. Co-manipulated systems enhance dexterity while maintaining direct clinical supervision. Single-arm flexible systems offer dexterity akin to a micro-sized wrist and increased capacity for interventions, though control is counterintuitive. The goal is to create micro-precise robotic tools to replace lost cells in the retina for conditions like macular degeneration.

1. Image-guided vitreoretinal robots:
Micro-precise systems for retinal therapy delivery
Christos Bergeles
Robotics and Vision in Medicine Lab
School of Biomedical Engineering and Imaging Sciences
King’s College London
In collaboration with Moorfields Eye Hospital and UCL Institute of Ophthalmology

2. Losing central vision
2
600,000 with Age-Related Macular Degeneration sight-loss in the UK alone
Normal vision Dry AMD RPE degradation

3. State of the art in cellular therapeutics
• The problem: cell loss replace lost cells
3
Day 45
Whole EB
Multiple delivery sites/layers
Healthy retina
Diseased retina

4. Challenge in manually delivering therapies
4

5. 6
Robots for retinal regenerative therapy delivery

6. Modelling
Co-manipulated robots: design, modelling, control
Design Safe Control
Mamplekos-Alexiou et al., ICRA 2018

7. Requirements-driven VR-assisted robot design
• Respect constraints:
– Operating room
– Surgical scenario
– Patient anatomy,
ergonomics
• Evaluate early:
– VR for OR navigation
– In silico mechanic
evaluation
– Via 3D printing
• Stay application focused:
– Occam's razor
– Develop dedicated
technology
Mamplekos-Alexiou et al., ICRA 2018

8. Requirements-driven VR-assisted robot design
• Respect constraints:
– Operating room
– Surgical scenario
– Patient anatomy,
ergonomics
• Evaluate early:
– VR for OR navigation
– In silico mechanic
evaluation
– Via 3D printing
• Stay application focused:
– Occam's razor
– Develop dedicated
technology
O’ Neill et al., CRAS 2019

9. Flexible robotic tools for therapeutics delivery
• Challenges
– Hard to fix a fulcrum point
– Straight tools do not enable dexterity
– Single point of entry deters manipulation
• Risks from conventional robotic tools
– Hypotony
– Intraocular lens damage
– Damage to the retina
10 Lin et al., EMBS 2015

10. Modelling
Flexible robots: design, modelling, control
Design Safe Control

11. Fundamental flexible robot architecture
• Pre-curve super-elastic tubes that conform to mutual shape
12

12. Robot control via manipulability shaping
• Maximizing manipulability as a secondary task in robot control
13
With manipulability control Without manipulability control
Khadem et al. ICRA 2019, submitted

13. Katie Test Slides

14. 15

15. 16
Concentric Tube Robot Kinematics
Coupling of Position and Orientation  Change of orientation requires
manipulation of many joints
 Robot body is required to change

16. Online stable inverse kinematics
• Telemanipulation of a concentric tube robot
– Attempt 1: Levenberg-Marquardt X
– Attempt 2: Nelder-Mead X (better)
– Attempt 3: …
• Different optimisers worked for different configurations
• How to find the best optimiser?
– Run all of them in parallel
– Keep the one that gives the best result
*

17. Leveraging Multi-Core Processor Architecture
*

18. 21
Comparison of inverse kinematics solvers

19. 22
From input device to simulation

20. 23
From manual actuation to simulation

22. 25
Design framework for robot design
Robot model
Design
optimisation
Surgical tasks
Anatomical volume
and constraints
Bergeles et al., TRO 2015

23. Designing dextrous continuum robots
26

24. Active constraints for operator guidance
*
• Frictional constraints (forbidden regions)
– Time-discrete elasto-plastic friction model
– Dissipate kinetic energy introduced by operator
– Use kinetic energy to guide operator
– Prevent autonomous robot motion
– Ensure stable robot control
• Guiding active constraints
– Smooth force profile
– Attractive forces to target or safe zones
Frictional Constraints

25. Summary
• Development of systems each with different advantages
– Co-manipulated system
• Ease of integration in clinical workflow
• Direct clinical supervision
• Enhances dexterity but still constrained by remote centre of motion
– Single arm flexible system
• Dexterity akin to a micro-sized wrist
• Increased capacity for challenging interventions
• Counterintuitive control
28

26. Image-guided vitreoretinal robots:
Micro-precise systems for retinal therapy delivery
@rvimlab
www.rvim.online