Drones for computer vision applications (Summer School)
Academic Study Board of the Faculty of Engineering
Teaching language: English
EKA: T930021102
Censorship: Second examiner: Internal
Grading: Pass/Fail
Offered in: Odense
Offered in: Summer school (autumn)
Level: Bachelor
Course ID: T930021101
ECTS value: 5
Date of Approval: 06-12-2023
Duration: Intensive course
Version: Approved - active
Course ID
Course Title
ECTS value
5
Internal Course Code
Responsible study board
Administrative Unit
Date of Approval
Course Responsible
| Name | Department | |
|---|---|---|
| Kamilla Juel Sørensen | kjs@tek.sdu.dk | TEK Uddannelseskoordinering og -support |
| Preben Hagh Strunge Holm | prebenh@mmmi.sdu.dk | SDU Robotics |
Teachers
Programme Secretary
| Name | Department | City | |
|---|---|---|---|
| Susanne Bech Fogtmann | sfo@tek.sdu.dk | TEK Uddannelseskoordinering og -support |
Offered in
Level
Offered in
Duration
Mandatory prerequisites
Students must have passed no less than 70 ECTS on their bachelor or bachelor of engineering programme.
Recommended prerequisites
Basic experience in electronics and embedded systems recommended for drone and camera payload construction.
Basic experience in (Python) programming recommended for computer vision exercises.
Learning objectives - Knowledge
- Architecture and principal components of multirotor drones and camera payloads.
- Application of simple computer vision algorithms to RGB camera footage captured by a drone.
- Drone ethics.
Learning objectives - Skills
- Construction, calibration, and flight testing a basic multirotor drone.
- Interfacing of camera payloads.
- Development of simple computer vision algorithms.
- Operation of a multirotor drone while adhering to operating procedures and safety protocols.
Learning objectives - Competences
- Understand the principal requirements and design of drones and payloads for computer vision based applications.
- Participate in finding technical applicable solutions to monitoring drones for environmental monitoring and sustainable precision farming.
Content
This course will teach how to construct and fly drones for real-world applications based on computer vision. The students will work in teams of 3-4 students on lab exercises in drone hardware and software, computer vision algorithms, drone operations, and ethics. This leads to a mini project where the students construct a multirotor drone and a camera payload, fly the drone outdoors at the nearby national UAS Denmark test center, and then use the computer vision algorithms to post-process the recorded video footage. The students will also get presentations of state-of-the-art drone research and innovation.
Teaching Method
The course will be experimental with lectures to provide the underlining theory. The students will work in teams of 3-4 on theory and laboratory exercises. The exercise results will lead to a mini project where the students will design, construct and operate a multirotor drone and camera payload, and post-process video footage using computer vision algorithms.
Time of classes
Two weeks in August
Number of lessons
hours per week
Teaching language
Examination regulations
Exam regulations
Name
Exam regulations
Examination is held
At the end of the summer course.
Tests
Exam
EKA
T930021102
Name
Exam
Description
Grading is based on an overall assessment of:
- atttendance (80 %)
- individual report submitted before or on the last day
- group presentations
Form of examination
Oral examination
Censorship
Second examiner: Internal
Grading
Pass/Fail
Identification
Student Identification Card - Date of birth
Language
English
ECTS value
5
Additional exam information
The form of examination in the re-examination is the same as in the
ordinary examination except the requirement of 80% attendance which
is removed.
Additional information
Please note that registration for this elective course is binding. However, we recommend you apply for de-registration of Summer School courses if you do not pass your exams in June, leaving you to register for re-exams in August. Apply by filling out the form. Application of Exemption from the Deadline for Registration or De-registration for Courses
Enrolment is limited to 16 students. If more applicants than places, applicants who meet the mandatory requirements are prioritised according to the below selection criteria:
Engineering students from BSc Robot Systems Engineering who need this specific summer course in order to graduate
Engineering students from BSc Robot Systems Engineering and BEng Robot Systems Engineering
Other students from SDU-TEK provided the course is approved as an elective on their study programmes
Other students from SDU provided the course is approved as an elective on their study programmes
Other students from SDU-TEK with preapproval of credit transfer
Other students from SDU with preapproval of credit transfer
Note: If further selection criteria are needed this will be based on a first-come-first-served basis.
This course is identical with T930010101 and T930019101. Any used examination attempts will be transferred.