Course content

The course contains a selection of the following topics:

• Software for robotics
• Software interface to physical or simulated robots
• Configurations and spaces
• Rigid body motions
• Forward kinematics
• Numerical methods for optimization
• Velocity kinematics
• Inverse kinematics
• Closed chain kinematics
• Trajectory generation
• Path planning
• Motion planning
• Robot dynamics and force control

More details on the curriculum will provided during the start of semester.

Learning outcome

Knowledge

• The candidate can explain linear transformations for kinematics and dynamics.
• The candidate can explain numerical methods for optimization.
• The candidate can explain methods for solving inverse kinematics, trajectory generation, path planning, motion planning, and force control.
• The candidate can explain various aspects of robot dynamics.
• The candidate can compare aspects of all of the above and discuss strenghts and weaknesses.

Skills

• The candidate can demonstrate and apply methods for solving inverse kinematics, trajectory generation, path planning, motion planning, and force control on physical or simulated robots.
• The candidate can use digital tools for modelling, simulation, and visualization of robots.

Generell kompetanse

• The candidate can apply acquired knowledge and skills to new areas for solving complex problems and projects..
• The candidate communicate extensive independent work and masters the terminology within the field.
• The candidate can make informed decisions on choice of methods given certain specifications and/or requirements.
• The candidate can apply acquired skills related to project work in new projects.

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.

Further on evaluation

The final grade is based on an overall evaluation of the portfolio, which consists of a number of works delivered through the semester. The portfolio contains assignments that are carried out, digitally documented and submitted during the term. Both individual and team assignments may be given. Assignments are designed to help students achieve specific course learning outcomes, and formative feedback is given during the period of the portfolio. The re-sit exam is an oral exam.

Specific conditions

Recommended previous knowledge

• AIS1001 Mikrokontrollere
• AIS1002 Objektorientert programmering og algoritmer
• AIS2001 Industriell elektroteknikk

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 may also include English material. The book Modern Robotics: Mechanics, Planning, and Control ISBN-13: 978-1107156302 may be used as supplementing literature.