Recommended previous knowledge in electric motor drives - and analog and digital electro technologies.
On successful completion of the course, the student should be able to
arrange mathematical models of different measurement systems and implement these models for practical execution, and choose the necessary sensors
be able to transform the state variable (position/orientation, velocity and acceleration) between different Coordinate systems
understand and be able to set up kinematic models for mobile platforms
have knowledge of the most common sensors and systems for positioning and navigation
be able to implement algorithms for sensor fusion
This course covers instrumentation for mobile platforms, including sensor kinematics, as well as provides an overview of the sensor and measurement system for positioning and navigation of mobile platforms. The course will also contain use of laser measurement equipment, scanners for high precision surface- and position measurement. The course will provide insight into some algorithms for sensor fusion, where multiple parallel sensors are working together. Kalman filter and complementary filter will be implemented on an autonomous mobile platform that will be built as part of the project work.
Teaching methods and workload
Lectures, exercises, laboratory exercises, including project work in groups of two students. Estimated work load for the average student is approximately 200 hours.
Compulsory assignments must be approved in order to take the examination. Information will be given in Canvas at the start of the course.
Assessment methods and criteria
3-hour individual written examination under supervision (60 % of the final assessment) and practical project work (40 % of the final assessment). Graded assessment.
Course evaluation is carried out as a midterm evaluation in accordance with standard procedure in the quality assurance system, chapter 2.1.1., unless other information is given in the beginning of the semester.