Course in Autonomous Navigation for Agricultural Machinery
Online 300-hour course in autonomous navigation for agricultural machinery. 6 modules covering ISO 18497 (safety of highly automated agricultural machinery), ISO 25119 (functional safety of tractors and agricultural machinery) and ROS 2. Dedicated tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe the current state of autonomy in agricultural machinery.
Explain the perception and positioning systems in the field.
Configure remote supervision and machine connectivity.
Apply functional safety requirements and legal liability.
Evaluate the profitability and organisational impact of autonomy.
Analyse real cases of adoption and their lessons.
Design an implementation project for autonomous machinery.
Who it's for
- Agricultural robotics engineer who wants to specialise in autonomous navigation in agricultural machinery.
- Precision agriculture technician who wants to specialise in autonomous navigation in agricultural machinery.
- Functional safety specialist who wants to specialise in autonomous navigation in agricultural machinery.
- Innovation manager at farms who wants to specialise in autonomous navigation in agricultural machinery.
- Autonomous systems integrator who wants to specialise in autonomous navigation in agricultural machinery.
- Technical adviser at an agricultural dealership who wants to specialise in autonomous navigation in agricultural machinery.
- Engineering or science graduates seeking to join agricultural machinery manufacturers.
What you'll work with
- ISO 18497 (safety of highly automated agricultural machinery)
- ISO 25119 (functional safety of tractors and agricultural machinery)
- ISO 11783 (ISOBUS)
- Regulation (EU) 2023/1230 (machinery products)
- Regulation (EU) 2024/1689 (artificial intelligence)
- EN ISO 4254-1 (agricultural machinery, general safety requirements)
6 modules · 300 h
1.1Degrees of autonomy in agricultural machinery1.2Assisted guidance, autopilot and supervised autonomy1.3Tractors without cabs and crop robots1.4Tasks that are most mature for autonomy1.5Limitations of the agricultural environment1.6Seasonality and narrow working windows1.7Farmer expectations and product reality1.8Actors: manufacturer, integrator and farm1.9Fit within work organisation1.10Workshop: feasibility diagnosis on a farm
2.1Satellite positioning and corrections2.2Line navigation and repeatability2.3Perception: cameras, lidar and radar2.4Detection of obstacles, people and animals2.5Crop and row recognition2.6Dust, rain, mud and low-angle light2.7Sensor fusion and degradation2.8Field maps and geofences2.9Path planning and turns2.10Practice: analysis of a perception failure
3.1Supervision station and required level of attention3.2On-site versus remote supervision3.3Control and alarm interface3.4Field connectivity and no-coverage modes3.5Mission logging and traceability3.6Control handover and remote stop3.7Several machines per supervisor3.8Cybersecurity of the connected machine3.9Updates and version management3.10Practice: configuration of a supervised mission
4.1Risk analysis of autonomous operation4.2Safety functions and stopping in a safe state4.3Exclusion zones and field signage4.4Presence of third parties: tracks and field boundaries4.5Machinery regulations applied to autonomy4.6Requirements for road travel and for working without an operator4.7Insurance and allocation of liability4.8Documentation required from the manufacturer4.9Incident investigation4.10Practice: risk assessment of a mission
5.1Cost of the technology and its depreciation5.2Labour savings and their real limit5.3Extending the working window5.4Effect on optimal machine size5.5Several small machines versus one large one5.6Staff training and new profiles5.7Maintenance of autonomous equipment5.8Usage and performance indicators5.9Project risks and mitigation5.10Practice: economic analysis of an adoption
6.1Autonomy in vineyards and orchards6.2Autonomy in arable crops6.3Weeding and seeding robots6.4Autonomy in on-farm internal logistics6.5Real cases and lessons learned6.6When to wait and when to adopt6.7Common mistakes in agricultural autonomy projects6.8Relationship with the manufacturer and support6.9Foreseeable evolution of the technology6.10Final project: autonomy adoption plan for a farm
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: Students progress at their own pace within the intake, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The Working Software is ROS 2, Gazebo, John Deere Operations Center, QGIS, in free, academic or evaluation versions. Tests are studied using real procedures for RTK guidance tests in the field, evaluation of obstacle detection systems and risk analysis of autonomous operation. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe the current state of autonomy in agricultural machinery.
Explain the perception and positioning systems in the field.
Configure remote supervision and machine connectivity.
Apply functional safety requirements and legal liability.
Evaluate the profitability and organisational impact of autonomy.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish-language proficiency to follow technical standards documentation.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours, spread over 3 to 5 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
The course uses ROS 2, Gazebo, John Deere Operations Center, QGIS. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An own diploma from SEIUM upon passing the continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are credited towards the advanced programme. Check the credit transfer policy when you enrol.
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