Grant: Alliance Grants

This is a research collaboration between MacDon Industries Ltd. and the University of Regina. The objective of this research is to implement precision agriculture techniques by leveraging data acquired through onboard sensors on crop-harvesting machines, with the aim of optimizing crop yield. The field-acquired information will be employed within a flexible-autonomy framework, where operators of the harvesting machines are provided with the data through user-friendly interfaces. This assists operators in making accurate and timely decisions during the harvesting process. The research project revolves around three key components. Firstly, there is image enhancement, where images are improved through the use of light-polarizing and band-pass color filters. Image processing methods will also be applied to enable accurate discrimination of crop colors. Secondly, the image-based metric measurement module is employed to extract measurements in both the physical and color spaces. These measurements are crucial for real-time perception and analysis. The third component focuses on optimal high-level motion planning. Motion planning strategies will be developed based on the metric and color measurements obtained from the field, as well as the kinematic and dynamic capabilities of the harvesting machine. An objective function, formulated as a weighted sum of factors such as task completion time, power consumption, and fuel usage, will be optimized in this process. By combining these components, the research aims to enhance crop harvesting efficiency by enabling accurate color discrimination, extracting meaningful metrics, and implementing optimal motion planning and control strategies. Our research would help with training HQP, who are critically needed in the industry.