Liyou Zhou
Research Interests
SLAM, NERF, VLA models.
Publications
Zhou, L., Ali, O., Arnaud Soumo, E., Attenborough, E., Swindell, J., Davies, J., & Fox, C. (2025). 3D Printer Based Open Source Calibration Platform for Whisker Sensors. In: Huda, M.N., Wang, M., Kalganova, T. (eds) Towards Autonomous Robotic Systems. TAROS 2024. Lecture Notes in Computer Science, vol 15051. Springer, Cham. [December 2024].
Zhou, L., Sinavski, O., & Polydoros, A. (2024) Robotic Learning in your Backyard: A Neural Simulator from Open Source Components, 2024 Eighth IEEE International Conference on Robotic Computing (IRC). [December 2024].
Presentations
“Exploration of LLM-Enhanced State-Machine function-calls for Planning Robot Actions” (oral) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands.
“Splat Gym: A Neural Simulator Environment for Training Fruit Picking Robots” (poster) – AgriFoRwArdS CDT Summer School: Robotic Phenotyping [July 2024] – Wageningen, The Netherlands.
“Robot Learning” – AgriFoRwArdS CDT Quarterly PhD Research Progress Meeting & new student welcome [October 2024] – Cambridge, UK.
“A Neural Simulator from Open Source Components” (oral) – IEEE International Conference on Robotic Computing (IRC) 2024 [December 2024] – Online.
“How to use Generative Models as Robot Simulators” (oral) – AgriFoRwArdS Seminar Day and Quarterly Research Progress Meeting [December 2024] – Lincoln, UK.
“Towards bimanual fruit manipulation: 2 different approaches to the same end” (oral) – AgriFoRwArdS CDT Annual Conference 2025 [May 2025] – Online.
Other activities
- Nominated for the ‘Best Student Paper’ award at the IEEE International Conference on Robotic Computing (IRC) 2024 [December 2024].
- Winner of the ‘Best Student Opponent’ award at the IEEE International Conference on Robotic Computing (IRC) 2024 [December 2024].
About me
I have a background in autonomous driving and IoT software development. I have been a long-time proponent and contributor of the ROS ecosystem. I am interested in exploring the emerging world of end-to-end machine learning in robotics through the CDT. I am eager to learn more about the agriculture domain area and the many opportunities for optimisation and disruption advanced robotics can bring
MSc Project
Robot Learning in Neural Simulator for fruit picking
- Quickly build a 3D training environment from few images.
- Photo realistic rendering.
- Infer missing information such as partially occluded fruits.
- Curate an experimental dataset of robot pose and high resolution images.
- Construct a 3d scene using neural representation.
- Demonstrate the ability to train a control policy in simulation.
- Transfer the learning to real-world by running scenarios in the real world robot.
PhD Project
AgriVision 2.0: Vision Language Action Robotics in Agriculture
With the advent of machine learning, purely modeless data driven robotic planning and control becomes a reality. Advanced capabilities are shown to be possible with self-supervised learning from data. Techniques such as Reinforcement Learning, world modelling, generative AI and language models have been successfully applied to robotics to solve a range of complex tasks. I intend to develop advanced robotic learning techniques in the specific context of agriculture applications. Innovation can be derived from the novel applications and push the boundaries of robotic capabilities and deployment in agriculture.
Liyou’s PhD project is being carried out in collaboration with Wayve Technologies Ltd, under the primary supervision of Dr Sebastian Pattinson.