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Master'sRobotics, Automation & Control Applications open

Master’s in Advanced Manipulation Engineering

Online master's programme of 1,900 hours in advanced manipulation engineering. 12 modules covering manipulator kinematics and dynamics, motion planning, grippers, grasp theory, perception, contact-rich manipulation, robot learning, complex objects, safety and industrial integration under ISO 10218-1:2025, ISO 10218-2:2025 and ISO/TS 15066:2016, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
Enrol now View syllabus Ask an advisor
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Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.

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Learning outcomes

What you will be able to do

01

Solve the kinematics and dynamics of manipulators.

02

Plan collision-free motions.

03

Select and design end-effectors.

04

Evaluate grasp quality with contact models.

05

Integrate 3D perception into manipulation tasks.

06

Apply learning techniques to manipulation.

07

Validate the safety of manipulation applications.

Profile

Who it's for

  • Robotic manipulation engineers.
  • Robotics developers working with ROS 2.
  • Vision specialists for manipulation.
  • Robotic cell integrators.
  • Robotics researchers.
  • Robot applications engineers.
  • Engineering or science graduates aiming to enter the automotive sector.
Standards & tools

What you'll work with

  • ISO 10218-1:2025 (safety requirements for industrial robots)
  • ISO 10218-2:2025 (safety of robot applications and cells)
  • ISO/TS 15066:2016 (collaborative robot safety)
  • ISO 9409-1:2004 (robot mechanical interfaces – flanges)
  • ISO 9283:1998 (robot performance criteria and test methods)
  • ISO 13849-1:2023 (safety-related parts of control systems)
  • Directive 2006/42/EC (EU Machinery Directive)
  • MoveIt 2
  • ROS 2
  • RoboDK
  • MuJoCo
  • PyBullet
Syllabus

12 modules · 1900 h

  1. 1.1. Orientation representation and quaternions
  2. 1.2. Denavit-Hartenberg parameters
  3. 1.3. Forward kinematics of serial robots
  4. 1.4. Analytical and numerical inverse kinematics
  5. 1.5. The Jacobian and joint velocities
  6. 1.6. Singularities and manipulability
  7. 1.7. Redundant 7-axis robots
  8. 1.8. Parallel and delta robots
  9. 1.9. Workspace and reach
  10. 1.10. Lab: inverse kinematics of a 7-axis arm
  1. 2.1. Lagrange and Newton-Euler formulations
  2. 2.2. Identification of dynamic parameters
  3. 2.3. Joint PID control
  4. 2.4. Computed torque control
  5. 2.5. Impedance and admittance control
  6. 2.6. Gravity and friction compensation
  7. 2.7. Trajectory tracking in Cartesian space
  8. 2.8. Torque and velocity limits
  9. 2.9. Collaborative robots and force control
  10. 2.10. Practical: dynamic identification of an arm
  1. 3.1. Joint and Cartesian interpolation
  2. 3.2. Trapezoidal and S-curve profiles
  3. 3.3. Time-optimal parameterisation with TOPP-RA
  4. 3.4. Collision detection with FCL
  5. 3.5. OMPL planners in MoveIt 2
  6. 3.6. Trajectory optimisation with CHOMP and STOMP
  7. 3.7. Orientation constraints
  8. 3.8. Real-time planning
  9. 3.9. Coordinated motion with external axes
  10. 3.10. Workshop: planning with MoveIt 2
  1. 4.1. Parallel and angular grippers
  2. 4.2. Electric versus pneumatic grippers
  3. 4.3. Suction cups and vacuum generators
  4. 4.4. Adaptive and underactuated grippers
  5. 4.5. Multi-fingered robotic hands
  6. 4.6. Magnetic and electroadhesive grippers
  7. 4.7. Tool changers
  8. 4.8. Custom finger design
  9. 4.9. Selection by part and cycle time
  10. 4.10. Case study: finger design for a complex part
  1. 5.1. Point contacts with friction
  2. 5.2. Grasp matrix and force closure
  3. 5.3. Form closure and stability
  4. 5.4. Grasp quality metrics
  5. 5.5. Grasping deformable objects
  6. 5.6. Precision and power grasps
  7. 5.7. In-hand manipulation
  8. 5.8. Controlled sliding and rolling
  9. 5.9. Tactile sensors in fingers
  10. 5.10. Practical: force-closure analysis
  1. 6.1. Hand-eye camera calibration
  2. 6.2. 6D object pose estimation
  3. 6.3. Instance segmentation
  4. 6.4. Point clouds and CAD model registration
  5. 6.5. Grasp detection with neural networks
  6. 6.6. GraspNet and Dex-Net
  7. 6.7. Visual object tracking
  8. 6.8. Image-based visual servoing
  9. 6.9. Handling transparent and shiny objects
  10. 6.10. Lab: bin picking with a 3D camera
  1. 7.1. Peg-in-hole insertion with clearances
  2. 7.2. Hybrid force-position control
  3. 7.3. 6-axis force-torque sensors
  4. 7.4. Assembly with tight tolerances
  5. 7.5. Robotic screwdriving with torque control
  6. 7.6. Polishing and deburring with controlled force
  7. 7.7. Spiral search strategies
  8. 7.8. Contact and collision detection
  9. 7.9. Passive compliance with RCC devices
  10. 7.10. Practical: insertion with force control
  1. 8.1. Learning from demonstration
  2. 8.2. Movement primitives: DMP and ProMP
  3. 8.3. Reinforcement learning in manipulation
  4. 8.4. Sim-to-real and domain randomisation
  5. 8.5. Diffusion policies for manipulation
  6. 8.6. Vision-language-action models
  7. 8.7. Manipulation datasets
  8. 8.8. Teleoperation for data capture
  9. 8.9. Generalisation to new objects
  10. 8.10. Lab: learning from demonstration in simulation
  1. 9.1. Deformable objects: cables and textiles
  2. 9.2. Handling bags and packaging
  3. 9.3. Handling fragile food products
  4. 9.4. Destacking and separating parts
  5. 9.5. Reorienting parts by pushing
  6. 9.6. Non-prehensile manipulation
  7. 9.7. Mobile manipulation with AMR bases
  8. 9.8. Dual-arm coordination
  9. 9.9. Manipulation in unstructured environments
  10. 9.10. Case study: cable manipulation
  1. 10.1. ISO 10218-1 and 10218-2
  2. 10.2. Technical specification ISO/TS 15066
  3. 10.3. Power and force limiting
  4. 10.4. Speed and separation monitoring
  5. 10.5. Risk assessment of applications
  6. 10.6. Safety of grippers and workpieces
  7. 10.7. Validation of safety functions
  8. 10.8. Design of collaborative cells
  9. 10.9. Measuring collision forces
  10. 10.10. Practical: cell risk assessment
  1. 11.1. Offline programming with RoboDK
  2. 11.2. ROS 2 interfaces with industrial controllers
  3. 11.3. Communication with PLCs
  4. 11.4. Cycle-time calculation
  5. 11.5. Cell and TCP calibration
  6. 11.6. Robustness to part variability
  7. 11.7. Monitoring failed grasps
  8. 11.8. Commissioning and validation
  9. 11.9. Maintenance of manipulation cells
  10. 11.10. Case study: robotic assembly cell
  1. 12.1. Definition of the manipulation task
  2. 12.2. Selection of robot and end-effector
  3. 12.3. Perception system and calibration
  4. 12.4. Grasp strategy and planning
  5. 12.5. Control implementation
  6. 12.6. Experimental or simulated validation
  7. 12.7. Analysis of success rate and cycle time
  8. 12.8. Conclusions and future work
  9. 12.9. Master's Thesis report
  10. 12.10. Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

A 100% online programme on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it fits alongside your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is MoveIt 2, ROS 2, RoboDK, MuJoCo and PyBullet, in free, academic or evaluation versions. Exercises are based on real procedures: grasping parts with a 3D camera, insertion with force control, and learning from demonstration in simulation. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO 10218-1:2025, ISO 10218-2:2025, ISO/TS 15066:2016, ISO 9409-1:2004, ISO 9283:1998, ISO 13849-1:2023, Directive 2006/42/EC.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 10218-1:2025, ISO 10218-2:2025 and ISO/TS 15066:2016 applied to real cases, not as a theoretical annex.
Industry software:MoveIt 2, ROS 2, RoboDK, MuJoCo and PyBullet, in free, academic or evaluation versions.
Master's Thesis with defence:A complete advanced manipulation application, from robot and end-effector selection and perception to grasp planning, control and validation, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Define the task
Define the manipulation task and select the robot and end-effector.
Build the perception system
Set up and calibrate the 3D perception system for object detection.
Plan grasps and motions
Design the grasp strategy and collision-free motion planning.
Implement and validate
Implement the control and validate experimentally or in simulation, measuring success rate and cycle time.
Master's Thesis
Present the manipulation application and its results in your Master's Thesis, defended before a panel.
Career opportunities

Where this takes you

Robotic Manipulation EngineerROS 2 Robotics DeveloperVision for Manipulation SpecialistRobotic Cell IntegratorRobotics ResearcherRobot Applications Engineer
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent proven professional experience.
  • Internet connection and a computer capable of running the programme software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with MoveIt 2, ROS 2, RoboDK, MuJoCo and PyBullet, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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