When: 16th of October, 1:00pm AEDT
Where: This seminar will be partially presented at the ACFR seminar area, J04 lvl 2 (Rose St Building) and partially online via Zoom. RSVP
Speaker: Dr Thien Hoang Nguyen
Title: Towards Autonomous In-situ Soil Sampling and Mapping in Large-Scale Agricultural Environments
Abstract:
Conventional soil sampling and laboratory analysis are slow, labour-intensive, and provide only coarse spatial resolution, limiting their usefulness for large-scale precision agriculture. In this talk, I will present a modular robotic system that autonomously collects, analyses, and maps key soil properties in near real time. The system combines a mobile soil sampling robot and a mobile wet-chemistry laboratory capable of measuring important soil properties, such as pH and macronutrients (N, P, K) directly in the field. Validated through multi-day field trials on large-scale Australian farms, the platform demonstrates a major step toward high-resolution, data-driven, real-time soil monitoring. I will also share key challenges and lessons learned from developing and deploying the system in real agricultural environments, highlighting the practical considerations for translating research prototypes into robust field-ready technologies.
Bio:
Dr. Thien Hoang Nguyen received his Ph.D. in Robotics from Nanyang Technological University (NTU), Singapore, in 2023, following a Bachelor of Engineering (Honours) in Electrical and Electronic Engineering from Ho Chi Minh City University of Technology, Vietnam, in 2017. He served as a Project Officer at NTU’s ST-Eng Corporate Lab (2017–2018) and later as a Research Fellow at the NTU Singapore’s Centre for Advanced Robotics Technology Innovation (CARTIN) (2023-2024). Since 2024, Dr. Nguyen has held the position of Vonwiller Postdoctoral Research Associate in Robotics and AI for Precision Agriculture at the Australian Centre for Robotics (ACFR), University of Sydney. Dr. Nguyen’s research focuses on autonomous field robotics, multi-modal sensor fusion, optimisation, and AI algorithms for precision agriculture. He currently leads the Integrated AgriSense project, which advances the integration of heterogeneous robotic platforms, IoT sensor networks, and digital twinning. This multidimensional approach enables real-time mapping and analysis of macronutrient and water distribution across agricultural landscapes.