Presentations

• “Analysis of Adaptive Passive Technologies for the Locomotion and Inspection with Autonomous Robots in Unstructured Environments” (poster) – AgriFoRwArdS CDT Annual Conference 2024: Robots in Action [July 2024] – Norwich, UK.
• “SLAM (Simultaneous localisation and mapping)” (oral) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands.
• “Analysis of Adaptive Passive Technologies for the Locomotion and Inspection with Autonomous Robots in Unstructured Environments” (poster) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands.
• “Open-source hardware whisker sensor” (oral) – Towards Autonomous Robotic Systems (TAROS) 2024 [August 2024] – London, UK.
• “The AgriFoRwArdS CDT Summer School – Ground Navigation/SLAM for creating weed/plant maps (Theme 4)” (oral) – Towards Autonomous Robotic Systems (TAROS) 2024 [August 2024] – London, UK.

Activities and Outputs

• Represented the AgriFoRwArdS CDT at the University of Lincoln’s stand at CropTec 2023 – showcasing research and communicating with the public [November 2023] – Stoneleigh, UK.
• Discussion Panel member at Towards Autonomous Robotic Systems (TAROS) 2024 – Discussion topic: Challenge-driven Postgraduate Training [August 2024].

About me

I have always been interested in robotics and building things but have sometimes struggled to see the applications for robots for uses other than manufacturing. However, by joining the CDT I feel there will be plenty opportunities to explore this within agriculture. 

I am also looking forwards to living in Lincoln, as it will mark the start of a new chapter in my life after I spent the last 4 years living in Norwich completing an MComp in Computer Science at UEA, during which I worked on two robotics related projects.

As I mentioned before “I have always been interested in robotics and building things” and that has not changed much because during my spare time I will be tinkering with some sort of electronics/robot related project with a more “recreational” focus.

However, when not tinkering with tech, I do like to spend some time listening and play music, as I also play bass. 

MSc Project

Analysis of Adaptive Passive Technologies for the Locomotion and Inspection with Autonomous Robots in Unstructured Environments

This project focuses on developing and testing adaptive passive technologies to enhance robotic movement in challenging, unstructured environments.

One key aspect of the research is the evaluation of the Passively-Transformable Single-Part Wheel (PaTS-Wheel) and our modified version, the “DogBone-PaTS-Wheel” (or DogBone Wheel). By measuring energy efficiency, vibration, and traversal performance through a robotic test platform, we observe how the technology can improve the robot’s ability to handle difficult terrains and obstacles. Notably, the PaTS-Wheel maintains competitive energy usage, with less than a 5% difference compared to a more traditional wheel in some scenarios.

These findings suggest that adaptive passive wheel technologies hold potential in advancing robotic applications in rough environments, and through research we might see improvements that could lead to even greater efficiency and performance gains across a wide range of applications.

PhD Project

Autonomous robot-based precise soil sampling for PCN infield analysing and mapping

Plant parasitic nematodes, like Potato Cyst Nematode (PCN), are one of the largest groups of pathogens for crops/plants that can seriously impact food security and lead to losses in production.

This project aims to tackle the impacts of PCN on the potato industry and the issues surrounding the excessive use of nematicides in the surrounding environment. By applying the use of an infield autonomous soil sampling and processing system to rapidly prepare more individual soil samples and using a series of image processing techniques to detect, map and predict the PCN population in a potato crop field, we can work towards reducing the application of mass chemical control methods, like nematicides, and enable for more precise application on areas of interest to mitigate against further crop yield losses by the presence of PCN in the field.

This data is used to map the distribution of the estimated PCN population via the geo-referenced samples from the field, enabling farmers to make for rapid responses to infestation by providing faster processing results instead of sending samples from the field to the lab. A key advantage is that the infield processing system can handle each sample individually, which would be costly if done using traditional lab analysis to get an accurate enough prediction of the current PCN distribution mapped out and used to inform farmers about their field’s state.

Primary Supervisor: Dr Alexandr Klimchik – University of Lincoln

Secondary Supervisor: Dr Sebastian Pattinson – University of Cambridge