Publications

• Rogers, H. and Fox, C. (2020) ‘An Open Source Seeding Agri-Robot‘, UKRAS20 Conference: Robots into the real world Proceedings.
• Rogers, H., Dawson, B., Clawson, G., and Fox., C. (2021) ‘Extending an Open Source Hardware Agri-Robot with Simulation and Plant Re-identification‘, Oxford Autonomous Intelligent Machines and Systems Conference 2021.
• Rogers, H., De La Iglesia, B., Zebin, T., Cielniak, G., Magri, B. (2023). An Automated Precision Spraying Evaluation System. Towards Autonomous Robotic Systems. TAROS 2023: Lecture Notes in Computer Science, 14136. Springer, Cham.
• Rogers, H., De La Iglesia, B., Zebin, T., & Cielniak, G. (2023) An Agricultural Precision Sprayer Deposit Identification System, 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE), Auckland, New Zealand, 2023, pp. 1-6.
• Rogers, H., De La Iglesia, B., & Zebin, T. (2023) Evaluating the Use of Interpretable Quantized Convolutional Neural Networks for Resource-Constrained Deployment, Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 1, pp.109-120.
• Rogers, H., De La Iglesia, B., Zebin, T., Cielniak, G., & Magri, B. (2024) Deep Learning for Precision Agriculture: Post-Spraying Evaluation and Deposition Estimation. Pre-print.

Presentations

• “Robotics Manipulators in Agriculture: A Brief Review” (oral) – International Conference on Robotics and Automation (ICRA) Task-Informed Grasping Workshop – III [May 2021] – Online.
• “RAS Counter: Non-invasive yield prediction for vineyards” (oral) – AgriFoRwArdS CDT Summer School 2021 [June 2021] – Online.
• “Extending an Open Source Hardware agri-robot with simulation and plant re-identification” (oral) – Joint Robotics and Autonomous Systems CDT Conference 2021 [October 2021] – Online.
• “Explainable Droplet Recognition System for Precision Sprayer Applications” (poster) – Joint Robotics and Autonomous Systems CDT Conference 2022 [June 2022] – Bristol, UK.
• “Explainable Droplet Recognition System for Precision Sprayer Applications” (oral) – AgriFoRwArdS CDT Annual Conference [June 2022] – Lincoln, UK.
• “Fish Sorting: A whatsinyour.net solution” (oral) – AgriFoRwArdS CDT Summer School 2022 [July 2022] – Norwich, UK.
• “Explainable Droplet Quantification System for Precision Sprayer Applications” (poster) – University of East Anglia Computing Sciences Postgraduate Showcase Day 2022 [October 2022] – Norwich, UK.
• “The Preparation and dish up of an English Breakfast with Robots” (oral) – AgriFoRwArdS CDT Summer School 2023 [March 2023] – Lincoln, UK.
• “An Automated Agricultural Precision Sprayer Identification And Localisation Evaluation System” (poster) – University of East Anglia Computing Sciences Postgraduate Showcase Day 2023 [May 2023] – Norwich, UK.
• “An Agricultural Precision Sprayer Deposit Identification System” (oral) – 19th IEEE International Conference on Automation Science and Engineering (IEEE CASE 2023) [August 2023] – Auckland, New Zealand.
• “An Automated Precision Spraying Evaluation System” (oral) – Towards Autonomous Robotic Systems (TAROS) 2023 / AgriFoRwArdS CDT Annual Conference 2023 / Joint Robotics CDT Annual Conference 2023 [September 2023] – Cambridge, UK.
• “Closing the Loop on Precision Spraying” (poster) – Towards Autonomous Robotic Systems (TAROS) 2023 / AgriFoRwArdS CDT Annual Conference 2023 / Joint Robotics CDT Annual Conference 2023 [September 2023] – Cambridge, UK.
• “Title Unknown” (oral) – Syngenta industry visit [October 2023] – Bracknell, UK.
• “Evaluating the Use of Interpretable Quantized Convolutional Neural Networks for Resource-Constrained Deployment” (oral) – International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR) [November 2023] – Rome, Italy.
• “Title Unknown” (oral) – Syngenta industry visit [December 2023] – Bracknell, UK.
• “Closing the Loop on Precision Spraying” (oral) – University of East Anglia Weekly Seminar Series [March 2024] – Norwich, UK.
• “Q&A for Industry Sponsors” (oral) – UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial INtelligence (SUSTAIN) Industry Event [June 2024] – Online.
• “Closing the Loop on Precision Spraying” (oral) – Sensor CDT Challenge Mentor Event [June 2024] – Cambridge, UK.
• “Deep Learning for Precision Agriculture: Post-Spraying Evaluation and Deposition Estimation” (oral) – University of East Anglia Computing Sciences Postgraduate Research Day 2024 [June 2024] – Norwich, UK.
• “eXplainable AI Unveils Enhanced Training Strategies and Diverse Model Weight Visualisations” (poster) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands.
• “Beyond 2D images” (oral) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands.

Other Activities

• Member of the AgirFoRwArdS CDT Drink Outside the Box Organisation Committee.
• Ran a workshop titled “Extending an Open Source Hardware Agri-Robot with Simulation and Plant Re-identification” at the Oxford Autonomous Intelligent Machines and Systems Conference 2021 [October 2021] – Oxford, UK.
• LEGO Robots Outreach Sessions at UEA, Yarmouth College, Thetford Academy.
• Gave a career talk to potential PhD students at Ormistion Victory Academy – Norfolk, UK.

About me

My name is Harry, I joined the CDT in September 2020. Before this I was at the University of Lincoln completing a BSc in Computer Science looking to work in robotic software development. I am interested in robot vision, deep learning and robot navigation. During my undergraduate I published a paper about my dissertation project in which I built and programmed an agricultural robot, which dispensed seeds and was tracked via GPS.

During the MSc Robotics and Autonomous systems, I have worked part time on the BACCHUS project. This has been fun to be work on an actual project that will be deployed to have a system in a vineyard. I have also worked on a paper for ICRA Task-Informed Grasping Workshop with members from the CDT as well as the MSc. Finally, I have also helped setup the Drink Outside the Box as a member of the committee

MSc Project

An Empirical Comparison of Optimisation Methods for Embedded DNNs

Automated precision agriculture is imperative and needs help to be optimised. To enable this Deep Neural Networks (DNNs) need to be deployed to ensure precision is kept high. Deploying DNNs like a Faster R-CNN to complete object detection can outperform YOLO DNNs, however these are much more difficult to deploy due to the size of the DNN. This thesis completes an empirical comparison of optimisations and considers deployment on multiple different embedded devices. This thesis completes multiple types of testing on multiple types of embedded devices with differing backbones for a Faster R-CNN. This thesis discovers that when DNNs are deployed not all optimisations can optimise DNNs for embedded deployment. This thesis also finds that each embedded device tested had optimal results with different combinations of optimisations. This thesis also contributes the usage of multiple quantisation optimisations for a Faster R-CNN. When using the multiple quantisation methods there can be seen a DNN size reduction of 52.4% and 67% with accuracy increases of 0.2% and 0.3% for a MobileNetV3-Large backbone and ResNet18 backbone, respectively. The test data is object detection based and can be used for grape harvesting within agricultural robotics.

PhD Project

Closing The Loop on Precision Spraying.

Despite the very long history of pesticides and herbicides it was not really until the world war II end that there was widespread use of synthesised chemicals in agriculture. Since then, there have been considerable developments often due to unintended or modelled consequences which usually amount to toxicity to animals or organisms essential to the ecosystem. The modern farmer is expected to be on top of considerable advice and guidance. Despite these advances the modern approach is known as “spray and pray” to imply that however carefully the diluted the chemicals are, there are always unintended consequences. A much-touted alternative is precision spraying in which exactly the right toxin is delivered to exactly the right place at exactly the right time. The technology already exists for the delivery of precise quantities of fluids through jets or aerosols. The question is, how feasible is it to monitor and control such systems in the field? That is what this project is about. 

This project aims to incorporate improvements in Syngenta’s existing platforms for autonomous targeting of crops, weeds, pests, accurate dispensing of fluid. We will formulate quantifiable methodologies for post spraying effect monitoring to help Syngenta fulfil the regulatory guidelines for EU green deal. We will get access to the in-field/test equipment and relevant data (video/field maps) to build realistic and practical solutions in terms of precision spraying. 

Harry’s PhD project is being carried out in collaboration with Syngenta, under the primary supervision of Prof Beatriz De Le Iglesia.