course-details-portlet

AIS2105

Mechatronics and Robotics

Assessments and mandatory activities may be changed until September 20th.

Credits 7.5
Level Intermediate course, level II
Course start Spring 2027
Duration 1 semester
Language of instruction English and norwegian
Location Ålesund
Examination arrangement Portfolio

About

About the course

Course content

The course provides an introduction to mechatronics and robotics and includes a selection of the following topics:

  • Structure of robots and robot cells
  • Rotations and rigid body motion
  • Kinematics, dynamics, and robot motion
  • Joint and force control
  • Modeling and control of industrial robots
  • Programming and interfaces for physical and simulated systems
  • Robot simulation
  • End-effectors and end-of-arm tooling
  • Sensors and sensor fusion in robotic applications
  • Introduction to machine vision, with emphasis on robotics-relevant applications
  • Basic introduction to ROS2 (Robot Operating System 2)
  • Industry 4.0 and Design for Manufacturing

More information about the curriculum will be made available at the start of the semester.

Learning outcome

The candidate should be able to:

  • Possess broad knowledge of implementation in ROS2, including nodes, components, topics, services, actions, and URDF.
  • Parameterize ROS2 projects using parameters, configuration files, and launch files.
  • Use established frameworks and libraries in ROS2 such as RViz2, TF2, and MoveIt.
  • Program robot manipulators in ROS2.
  • Communicate a solution to an industrial problem where the solution involves mechatronic and/or robotic systems.
  • Discuss different application areas for robots, as well as potential advantages and challenges related to their implementation.
  • Apply design and engineering principles for mechatronic and robotic systems under realistic conditions.
  • Analyze a solution involving a mechatronic and/or robotic system.
  • Calculate position and velocity for a general robot manipulator.
  • Solve the inverse kinematics problem for specific robot manipulators.
  • Generate smooth motions for robot manipulators and implement them in software.
  • Calculate and program simple grasping tasks for robot manipulators.
  • Explain and demonstrate the use of fundamental concepts in robotics and machine vision, such as kinematics, dynamics, path planning, rigid-body motion, grippers, sensors, sensor fusion, pinhole model, projective geometry, image processing, and ROS2.
  • Use machine vision to estimate the position of objects.
  • Program a robot to perform actions using machine vision.
  • Design, build, and test simple mechatronic systems, including software, control systems, sensors, actuators, communication protocols, and hardware.
  • Take responsibility for projects involving industrial robot arms or mobile robots.
  • Develop large-scale ROS2 projects that integrate multiple packages.
  • Present mechatronic/robotic systems through documentation of code and written reports.

Learning methods and activities

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.

Compulsory assignments

  • Compulsory activities

Further on evaluation

(the information may be changed until June 15th)

The final grade is based on an overall evaluation of the portfolio. The portfolio consists of work that is carried out and documented through digital submissions throughout the semester. A range of tasks is offered for the student to complete. Each task awards points, and the final grade is determined based on the number of points the student has accumulated during the semester on a scale from 0-100. It is possible to collect more than 100 points during the semester. Students are also encouraged to create their own point-earning tasks by agreement.

Both individual and group work may occur. The tasks are designed to help students achieve the desired learning objectives of the course, and feedback is provided along the way. For re-sit exams, an oral exam will be conducted in August.

Please note that this course also includes mandatory assignments that must be approved in order to be eligible to take the exam.

Specific conditions

Admission to a programme of study is required:
Automation and Intelligent Systems - Engineering (BIAIS)

Required previous knowledge

The course has no prerequisites.

It is a requirement that students are enrolled in the study programme to which the course belongs.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester and will typically also include English material.

Subject areas

  • Production Engineering - Advanced Robotics
  • Engineering Cybernetics
  • Engineering

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of ICT and Natural Sciences

Examination

Examination

Examination arrangement: Portfolio

Ordinary examination - Spring 2027

Portfolio
Grade Letter grades Weighting 100/100 Exam system Inspera Assessment

Examination arrangement: Oral exam (retake exam)

Re-sit examination - Summer 2027

Oral exam (retake exam)
Grade Letter grades Weighting 100/100