Publications

• Heiwolt, K., Mandil, W., Cielniak, G., & Hanheide, M. (2020) Automated Topological Mapping for Agricultural Robots. UKRAS20 Conference: “Robots into the real world” Proceedings, 27-29. [May 2020].
• Oppermann, L., Hirzel, S., Güldner., Heiwolt, K., Krassowski, J., Schade, U., Lange, C., & Prinz, W. (2021) Finding and analysing energy research funding data: The EnArgus system. Energy and AI, vol.5, 100070. [September 2021].
• Heiwolt, K., Duckett, T., & Cielniak, G. (2021) Deep Semantic Segmentation of 3D Plant Point Clouds. In: Fox, C., Gao, J., Ghalamzan Esfahani, A., Saaj, M., Hanheide, M., Parsons, S. (eds) Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science, vol 13054. Springer, Cham. [October 2021].
• Heiwolt, K., Öztireli, C., & Cielniak, G. (2023) Statistical shape representations for temporal registration of plant components in 3D. 2023 IEEE International Conference on Robotics and Automation (ICRA), 29 May 2023 – 02 June 2023, London, UK. [June 2023].
• Heiwolt, K., James, K., Sargent, D., & Ceilniak, G. (2024) Lincoln’s Annotated Spatio-Temporal Strawberry Dataset (LAST-Straw). Preprint. [March 2024].

Presentations

• “Semantic Segmentation of Plant Leaves from 3D Point Clouds using Deep Learning” (oral) – Lincoln Conference on Intelligent Robots and Systems 2020 [October 2020] – Online
• “Semantic-assisted 4D crop mapping” (oral) – Lincoln Agri-Robotics Mini Conference 2020 [December 2020] – Online
• “4D Scene Analysis for Autonomous Operation of Mobile Robots on Farms” (oral) – AgriFoRwArdS CDT Quarterly PhD Research Progress Meeting [January 2021] – Online
• “4D Crop Modelling” (oral) – University of Lincoln Postgraduate Research Showcase 2021 [February 2021] – Online
• “4D Scene Analysis for Autonomous Operation of Mobile Robots on Farms” (oral) – AgriFoRwArdS CDT Quarterly PhD Research Progress Meeting [April 2021] – Online
• “RAS Counter: Non-invasive yield prediction for vineyards” (oral) – AgriFoRwArdS CDT Summer School 2021 [June 2021] – Online
• “Using deep learning for semantic segmentation of 3D plant point clouds” (oral) – AgriFoRwArdS CDT Annual Conference 2021 [July 2021] – Online
• “RAS Counter: Non-invasive yield prediction for vineyards” (oral) – AgriFoRwArdS CDT Annual Conference 2021 [July 2021] – Online
• “Deep Semantic Segmentation of 3D plant point clouds” (oral) – Towards Autonomous Robotic Systems (TAROS) Annual Conference 2021 [September 2021] – Online
• “Deep Semantic Segmentation of 3D plant point clouds” (oral) – Joint Robotics and Autonomous Systems CDT Conference 2021 [October 2021] – Online
• “4D Scene Analysis for Autonomous Operation of Mobile Robots on Farms” (oral) – AgriFoRwArdS CDT Quarterly PhD Research Progress Meeting [May 2022] – Online
• “Reel-Bot” (oral) – AgriFoRwArdS CDT Summer School 2022 [July 2022] – Norwich, UK
• “Temporal Registration of Plant Parts in 3D” (oral) – 7th International Plant Phenotyping Symposium (IPPS) [September 2022] – Wageningen, The Netherlands
• “Statistical shape representations for temporal registration of plant components in 3D” (poster) – International Conference on Robotics and Automation (ICRA) 2023 [June 2023] – London, UK
• “Statistical shape representations for temporal registration of plant components in 3D” (poster) – Towards Autonomous Robotic Systems (TAROS) 2023 / AgriFoRwArdS CDT Annual Conference 2023 / Joint Robotics CDT Annual Conference 2023 [September 2023] – Cambridge, UK
• “Interview with fellow students: about you, your research, & the PhD experience” (oral) – AgriFoRwArdS CDT Quarterly PhD Research Progress Meeting & new student welcome [September 2023] – Lincoln, UK
• “SLAM (Simultaneous localisation and mapping)” (oral) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands
• “Semantic-assisted 4D Plant Modelling” (poster) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands

Other Activities

• Represented the AgriFoRwArdS CDT in the AgriFoRwArdS CDT promotional video, including interview about experiences within the CDT and the agri-food robotics sector
• Discussion Panel member at the AgriFoRwArdS CDT Annual Conference 2021 – Discussion topic: Tony Pridmore’s keynote talk “Plant Phenotyping: Getting to the root of the problem” [July 2021]
• Discussion Panel member at the AgriFoRwArdS CDT Annual Conference 2022 – Discussion topic: AgriFoRwArdS PhD research progress [June 2022]
• Represented the AgriFoRwArdS CDT at the University of Lincoln British Science Week school outreach event – showcasing research and robotic demonstrations to delegates [March 2022]
• Member of the AgriFoRwArdS CDT Drink Outside the Box Organisation Committee.
• Member of the AgriFoRwArdS CDT Advisory Board (March 2021 to November 2023).
• Member of the AgriFoRwArdS CDT Equality, Diversity and Inclusion (EDI) Panel (March 2022 to November 2023).
• Member of the AgriFoRwArdS CDT Student Panel (March 2022 to November 2023).
• Awarded Best Student Presentation at the AgriFoRwArdS CDT Annual Conference 2021 for ‘Using deep learning for semantic segmentation of 3D plant point clouds‘.
• Took part in the L-CAS Summer Undergraduate Student Project Scheme 2022

About me

My name is Karoline, I am from Germany, and I joined the CDT in September 2019. I have a background in neuroscience and robotics and I am especially interested in the research areas of 3D perception, sensor fusion, and mobile autonomy. I chose to join this CDT because the development of robots for agricultural applications offers many interesting real-world challenges that could have a great positive impact on a sustainable global food chain. I am currently working on my PhD with Grzegorz Cielniak at the University of Lincoln alongside a brilliant cohort of fellow PhD students with different backgrounds.

MSc Project

Semantic Segmentation of Plant Leaves from 3D Point Clouds using Deep Learning

In this project we aim to address the problem of semantically segmenting plant leaves from the background and other plant organs in three-dimensional point clouds of individual plants captured by RGBD sensors. Previous work utilises explicit prior knowledge about the expected plant morphology and sensor set-up, as well as manually tuned parameters to achieve this segmentation. Here we propose to train a supervised machine learning algorithm to predict the segmentation output directly from point cloud data and minimise the necessary user input.

PhD Project

4D Scene Analysis for Autonomous Operation of Mobile Robots on Farms

This research addresses challenges in 4D scene analysis for autonomous operation of mobile robots on farms. The deployment of agricultural robots will increase sustainability and support precision farming operations tuned to needs of individual plants. This research will enable robots to maintain precise 3D representations of uncertain and highly variable farm environments together with their semantics in order to safely traverse the farm autonomously, as well as to reconstruct structural representations of the crop. Additionally, registering these representations over time would allow for sustained crop monitoring and provide insight into spatio-temporal dynamics and interactions between the plants and environmental factors.

Karoline’s PhD project is being carried out in collaboration with Saga Robotics, and with primary supervision by Dr Grzegorz Cielniak.