Motion and manipulation


About this course

Motion and manipulation are key issues in the field of robotics and automation, but they also play a major role in virtual environments and games.
In this course models and planning problems for tasks that involve motion or manipulation are studied.
The course covers topics from kinematics, which studies motions without taking their causes into consideration.
The study of manipulation concentrates on kinematic models for articulated structures such as arms, models for grasp analysis based on velocities and forces, and on simple non-prehensile forms of manipulation such as pushing and elastic collisions.
Geometry is a major parameter in the definition, modeling, and planning of manipulation and motion tasks.

Course form
Lectures, practical sessions, and literature study, including individual and group presentations.


  • Chapters from the bookTheory of Applied Robotics by Reza N. Jazar.
  • Recent research articles from various robotics-related fields

Learning outcomes

After completing the course, the student:

  • has a broad overview of the area of robotics and the different subfields that exist.
  • knows the set-up of general robotic systems and their components, and is aware of common terminology and notation in the field.
  • knows about homogeneous coordinates and rigid transformations and their role in the kinematics of rigid objects.
  • is able to systematically assign coordinate frames to the links and joints of articulated structures to model the forward kinematics of such structures.
  • knows the main methods for inverse kinematics and is able to apply them.
  • knows the basic path planning problem and its most common extensions, and knows how to translate these path planning problems to configuration space.
  • knows about basic collision detection and elastic collisions.
  • knows what the role of Minkowski sums play in translational path planning, and has insight into the structure and complexity of the free part of the configuration space.
  • knows about temporal motion planning and prediction.
  • is able to implement a simple motion planning system which handles forward and inverse kinematics, and collision handling.

Written test, practical submissions, and literature submissions.
The grade for each item must be at least 5 and the average at least 5.5 to pass.

To qualify for a repair of the final result the mark needs to be at least a 4.

To follow this course, the students needs to

  • have a good foundation in calculus and linear algebra
  • be able to program in either Haskell or Python.

Required prior knowledge

You must meet the following requirements

  • Assigned study entrance permit for the master

Link to more information

  • Credits
    ECTS 7.5
  • Level
  • Contact coordinator
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