Novel visuo-tactile sensing mechanisms for soft tissue manipulation

To explore novel sensing and neuromorphic computing mechanisms for detailed robotic characterisation of soft tissue properties, motivated by medical robotics use cases
Description of the Project: 

Manipulation of soft tissues is an important part of many application areas, ranging from surgical systems to food processing and other manufacturing operations. In the surgical setting, there is a pressing need for new small form factor solutions that enable detailed characterisation of the continuum mechanics properties of tissues – something that is hard to do with off the shelf sensing systems. Incorporating such sensors within robots that can perform active model-based sensing would represent a step change towards generalisable autonomy in these application areas. 

We propose new approaches that combine: 

  1. 3D printed metamaterials that enable passive mechanical amplification of small deformations 
  1. Neuromorphic sensing systems including event based cameras 
  1. Physically-informed machine learning models for inversion of these measurements, and active steering of sensing, to achieve real-time high resolution sensing of continuum mechanical properties
Resources required: 
This project involves a combination of modelling, robotic implementation and collaboration with external colleagues
Project number: 
134003
First Supervisor: 
University: 
University of Edinburgh
Second Supervisor(s): 
First supervisor university: 
University of Edinburgh
Essential skills and knowledge: 
Strong knowledge of sensing and control in robotics, advanced vision and perception systems, as well as a good background in machine learning methods
Desirable skills and knowledge: 
Laboratory skills with mechanical and electronic systems, and the ability to combine modelling with experiment in tight iterative loops – we will need candidates who are comfortable with this full spectrum.
References: 

[1] Frenzel, T., Kadic, M., & Wegener, M. (2017). Three-dimensional mechanical metamaterials with a twist. Science, 358(6366), 1072-1074. 

[2] Katta, S., Krieg, M., & Goodman, M. B. (2015). Feeling force: physical and physiological principles enabling sensory mechanotransduction. Annual review of cell and developmental biology, 31, 347-371. 

[3] Straižys, A., Burke, M., & Ramamoorthy, S. (2020, May). Surfing on an uncertain edge: Precision cutting of soft tissue using torque-based medium classification. In 2020 IEEE International Conference on Robotics and Automation (ICRA) (pp. 4623-4629). IEEE. 

[4] Gallego, Guillermo, Tobi Delbruck, Garrick Orchard, Chiara Bartolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger et al. "Event-based vision: A survey." arXiv preprint arXiv:1904.08405 (2019).