Soil compaction is an important problem in modern agriculture. Agricultural machines tend to become larger and heavier which may severely damage soil structure, particularly if fields are worked under wet soil conditions. Two potential ways to mitigate soil compaction are (1) controlled traffic farming (CTF) where vehicles can only drive on pre-planned tracks, and (2) using smaller and lighter autonomous vehicles. Either of the solutions requires carefully planned paths over the field while they will also benefit from optimizing routes over those paths.
This project is a continuation of on-going research, both within projects and MGI thesis research on path planning for agricultural purposes. It is related to the recently granted project Field2Cover.The thesis topic can focus on software engineering aspects and/or application aspects of the work. Below you can find a non-exhaustive list of possible research objectives. We will cooperate with a commercial partner developing an autonomous vehicle for agricultural operations.
Objectives (choose from):
- Increase the efficiency and robustness of path and route optimization
- Include feasible turning manoeuvres in path planning, accounting for machine kinematics
- Path planning on sloping land
- Collision avoidance
- Assess usability of services
- Contribute to open source software library
- de Bruin, S., Lerink, P., Klompe, A., van der Wal, T., Heijting, S., 2009. Spatial optimisation of cropped swaths and field margins using GIS. Comput. Electron. Agric. 68 (2), 185–190.
- de Bruin, S., Lerink, P., J. La Riviere, I., Vanmeulebrouk, B., 2014. Systematic planning and cultivation of agricultural fields using a geo-spatial arable field optimization service: Opportunities and obstacles. Biosystems Engineering 120, 15-24.
- Jensen, M.F., Bochtis, D., Sørensen, C.G., 2015. Coverage planning for capacitated field operations, part II: Optimisation. Biosystems Engineering, 139, 149-164.
- Spekken, M., de Bruin, S., Molin, J.P., Sparovek, G., 2016. Planning machine paths and row crop patterns on steep surfaces to minimize soil erosion. Computers and Electronics in Agriculture, 124, 194-210.
- Several MGI theses
- Strong analytical skills
- Knowledge of Python scripting is a must
- Preferably some agronomic knowledge
Theme(s): Modelling & visualisation, Human – space interaction