Postgraduate Diploma in Automated Picking and Vision-Guided Robotics
Online 800-hour Postgraduate Diploma in Automated Picking and Vision-Guided Robotics. 8 modules covering ISO 10218-2:2025, EMVA 1288 Release 4.0 and OpenCV. Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Analyse picking processes suitable for automation.
Select 2D and 3D vision sensors.
Calibrate hand-eye systems with precision.
Apply neural networks to grasp detection.
Guide robots using vision in real time.
Integrate the picking cell with WMS and WCS.
Validate picking performance using real indicators.
Who it's for
- Machine vision engineer looking to specialise in Automated Picking and Vision-Guided Robotics.
- Picking robotics integrator looking to specialise in Automated Picking and Vision-Guided Robotics.
- AI engineer for robotics looking to specialise in Automated Picking and Vision-Guided Robotics.
- Logistics automation engineer looking to specialise in Automated Picking and Vision-Guided Robotics.
- Robot programmer looking to specialise in Automated Picking and Vision-Guided Robotics.
- Validation engineer looking to specialise in Automated Picking and Vision-Guided Robotics.
- Engineering or science graduates looking to enter e-commerce.
What you'll work with
- ISO 10218-2:2025
- EMVA 1288 Release 4.0
- GenICam (EMVA)
- ISO 9283:1998
- ISO 13849-1:2023
- GS1 General Specifications
- Reglamento (UE) 2024/1689 (Ley de IA)
8 modules · 800 h
1.1Picking processes in warehouses1.2Goods-to-person versus robot1.3Single-item and case picking1.4SKU variability1.5Rate and accuracy requirements1.6Robotic picking stations1.7Integration with automated warehouses1.8Picking indicators1.9E-commerce use cases1.10Workshop: analysis of a SKU assortment
2.1Industrial 2D cameras and lighting2.2Stereo vision and structured light2.3Time-of-flight cameras and their limitations2.4Point cloud segmentation in a container2.5Camera calibration2.6Sensor selection for picking2.7Reflections, transparencies and dark surfaces2.8Resolution and field of view2.9Fixed mounting versus arm-mounted2.10Practice: acquiring point clouds of a container
3.1Eye-in-hand calibration with a pattern3.2Eye-to-hand calibration with a fixed camera3.3Tsai-Lenz method3.4Calibration verification3.56D pose estimation3.6Registration with ICP and CAD models3.7Detection of boxes and parcels3.8Errors and their propagation3.9Recalibration in operation3.10Laboratory: hand-eye calibration with OpenCV
4.1Object detection with neural networks4.2Instance segmentation4.3Calculation of grasp points4.4Grasp networks: GQ-CNN and Contact-GraspNet4.5Vacuum versus gripper grasping4.6Picking from a cluttered container4.7Synthetic data for training4.8Continuous learning with production data4.9Grasp success metrics4.10Practice: vacuum grasp detection
5.1Robot guidance by vision5.2Coordinate conversion to the robot5.3Real-time trajectory correction5.4Image-based visual servoing5.5Collision-free approach planning5.6Commercial VGR systems5.7Integration with robot controllers5.8Perception cycle time5.9Detection failure management5.10Laboratory: robot guidance with a 3D camera
6.1Mechanical design of the station6.2Multi-tool grippers: vacuum–gripper6.3Communication with WMS and WCS6.4Part and quantity verification6.5Code reading and traceability6.6Cell safety6.7Exception and operator management6.8Camera and lighting maintenance6.9Replication across multiple picking stations6.10Case study: picking cell for pharmacy
7.1Testing with a real assortment7.2Success rate and picks per hour7.3Analysis of grasp failures7.4Robustness to new SKUs7.5Tuning vision parameters7.6Long-duration picking tests7.7Return on investment calculation7.8Assortment validation report7.9Continuous improvement of grasp models7.10Practice: picking failure analysis
8.1Definition of assortment and requirements8.2Selection of sensors and grippers8.3System calibration8.4Development of the perception pipeline8.5Robot integration8.6WMS integration8.7Performance validation8.8Picking technical report8.9Written report and presentation8.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: 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 OpenCV, Open3D, Halcon by MVTec, Photoneo PhoXi Control, NVIDIA Isaac Sim, in free, academic or evaluation versions. Tests are studied through real picking test procedures with a real assortment, hand-eye calibration and verification, and training with synthetic data. Assessment is continuous, module by 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.
Analyse picking processes suitable for automation.
Select 2D and 3D vision sensors.
Calibrate hand-eye systems with precision.
Apply neural networks to grasp detection.
Guide robots using vision in real time.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow the reading of technical regulations.
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 800 hours, spread over 6 to 8 months. That is an average of 10 to 15 hours a week, compatible with a full-time job.
You will work with OpenCV, Open3D, Halcon by MVTec, Photoneo PhoXi Control, NVIDIA Isaac Sim. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
SEIUM's own diploma upon passing continuous assessment and the integrating project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Check the recognition policy when enrolling.
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