Will’s research interests include, soft robotics, manipulation, human-robot collaboration, interaction.
- Rohde, W., & Forni, F. (2023) Lettuce modelling for growth control in precision agriculture. European Journal of Control, 2023, 100843, ISSN 0947-3580.
- AgriFoRwArdS CDT Annual Conference (2022): Regulation of plant growth in a field as a multi-agent control problem.
- University of Cambridge Division F Conference (2022): Precision Agriculture for Iceberg Lettuce.
- The Towards Autonomous Robots and Systems (TAROS) Conference 2023 / CDT Annual Conference / Joint Robotics CDT Conference (September 2023): Precision Agriculture: Controlling Crop Growth.
- Member of the AgriFoRwArdS CDT Advisory Board.
- Cohort 2 representative on the CDT Student Panel.
- University of Cambridge Demonstrator for third year labs.
I am particularly interested in soft robotics and manipulation, as well as human-robot collaboration and interaction.
Non-destructive mass estimation of Iceberg Lettuce
This project aims to develop a non-destructive mass estimation method for iceberg lettuce based on parameter estimation using the dynamic response of the plant to an input signal. Currently, in industry, the mass of an iceberg lettuce is measured destructively. A non-destructive method for mass estimation would enable measurements to be taken throughout a plant’s life to track growth.
Autonomous monitoring and control of crop growth as a feedback system
The project will model and control the growth of crops in an agricultural setting. The goal is to enable growers to maximise their harvest, by taking advantage of distributed sensing to optimise the use of fertilisers and of automation for crop management. The impact of the project will be the first direct application of feedback control to plant growth in an agricultural field.
Will will work through four work packages. The student will develop: (i) lettuce growth modelling as an open dynamical system, (ii) feedback control algorithms for crop optimization, (iii) distributed sensing technologies, (iv) automation for growth control. The student will take advantage of the facilities of the Department of Engineering of the University of Cambridge (Control prototyping lab, Agripods within the Observatory for Human-Machine Collaboration) and of the industry partner G’s growers (expertise, extensive databases, sensing technologies, automation).