ExjobbThesis Radar for Agricultural Machinery Applications — Investigation and Algorithm Development
ExjobbThesis Radar for Agricultural Machinery Applications — Investigation and Algorithm Development
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Sensors and their functions are fundamental components in the automation of agricultural machinery particularly for autonomous operation. By providing awareness of the machines surroundings processes and work results sensors enable advanced decision-making and control. This is essential for achieving higher levels of automation autonomy and efficiency in modern agriculture.
Väderstad AB is a Swedish agricultural equipment manufacturer specializing in high-performance tillage and seeding machinery. Their products are used worldwide to improve efficiency and precision in farming and the company is heavily involved in developing the next generation of smart and autonomous implements.
Radar sensors such as the newest generation from Acconeer have many potential applications in agricultural machinery. Examples include height estimation filling level monitoring clogging detection and soil aggregate quantification. While these sensors are highly capable their application and the interpretation of their outputs are not straightforward.
Goal:
This project pursues two related goals:
- To develop a detailed technical understanding of the application of radar sensors in agricultural machinery.
- To evaluate algorithms for application-specific interpretation of sensor outputs.
Proposed Tasks / and outcomes:
- Investigate sensor and application; build a simulation model.
Deliverable: Understanding of sensor signals and applications providing a foundation for further development. - Develop algorithms in Python:
- Based on signal processing
- Based on machine learning
Deliverable: Field-tested algorithms and performance measurements.
Implementation: Off-line analysis or as a ROS2 node
To succeed:
- Education at the Masters level (Civilingenjör) in Automatic Control Mechatronics or a related field.
- Familiarity with concepts such as sampled signals modulation convolution and correlation.
- Familiarity with machine learning.
- Advantage but not required: TSKS15 Detection and Estimation of Signals
Placement:
Väderstads Linköping office Linköping Science Park Mjärdevi Teknikringen 10
Contact:
Industrial Supervisor: Martin Hochwallner
Väderstad AB
Employment Type
Part-Time
