Introduction to Biologically-inspired Robotics and Learning (Summer School)

Academic Study Board of the Faculty of Engineering

Teaching language: English
EKA: T930008102
Censorship: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Summer school (autumn), Summer school (spring)
Level: Bachelor

Course ID: T930008101
ECTS value: 5

Date of Approval: 08-12-2020


Duration: Intensive course

Version: Archive

Course ID

T930008101

Course Title

Introduction to Biologically-inspired Robotics and Learning (Summer School)

ECTS value

5

Internal Course Code

SR-BRL

Responsible study board

Academic Study Board of the Faculty of Engineering

Date of Approval

08-12-2020

Course Responsible

Name Email Department
Kamilla Juel Sørensen kjs@tek.sdu.dk TEK Uddannelseskoordinering og -support, Det Tekniske Fakultet
Preben Hagh Strunge Holm prebenh@mmmi.sdu.dk Mærsk Mc-Kinney Møller Instituttet

Programme Secretary

Name Email Department City
Kirsten Thorup Nielsen kitho@tek.sdu.dk TEK Uddannelseskoordinering og -support, Det Tekniske Fakultet

Offered in

Odense

Level

Bachelor

Offered in

Summer school (autumn), Summer school (spring)

Duration

Intensive course

Mandatory prerequisites

Students should have some knowledge of Matlab and at least one of the following programming languages – C/C++ or Python. Basic knowledge of reading from sensors and control of motors used in mechatronics and robotics is a plus.

Overall learning objectives

Upon completion of the course, the student will be able to extract relevant principles of sensing,
control and learning from biological systems and apply them to technology.

Learning objectives - Knowledge

Having completed the course the successful student will have knowledge about:

  • Concepts in embodied artificial intelligence, neurorobotics and biorobotics
  • How biological neurons and their engineering models work
  • How biological learning in neurons and its engineering models work

Learning objectives - Skills

Having completed the course the successful student will be able to:

  • Construct simple neural brains for robots to solve a task
  • Apply biological learning algorithms to allow robots to learn

Learning objectives - Competences

Having completed the course the successful student will be able to:
  • Posing a robotic problem as a neural learning problem
    • Building appropriate neural brains to solve robotic problems

    Content

    • Biologically-inspired approaches to robotics - embodied artificial intelligence, neurorobotics and biorobotics
    • Biological neurons and their simplified engineering models
    • Simple artificial neural brains for sensing and control
    • Learning mechanisms in biological neurons and their simplified engineering models
    • Learning in artificial neural brains
    • Group project

    URL for Skemaplan

    Teaching Method

    Lectures, computer simulation exercises, group project work.

    Time of classes: two weeks in  August. 

    Number of lessons

    hours per week

    Teaching language

    English

    Examination regulations

    Exam regulations

    Name

    Exam regulations

    Examination is held

    At the end of the course

    Tests

    Exam

    EKA

    T930008102

    Name

    Exam

    Description

    The examination is based on an overall assessment of:
    • Attendance (80%)
    • Group project presentation

    Form of examination

    Oral examination

    Censorship

    Second examiner: Internal

    Grading

    7-point grading scale

    Identification

    Student Identification Card - Date of birth

    Language

    English

    ECTS value

    5

    Additional information

    Please note that registration for this elective course is binding.

    Enrolment is limited to 10 students. If more applicants than places, applicants who meet the mandatory requirements are prioritised according to the below selection criteria:

    • Engineering students from BSc in Robot Systems Engineering and BEng in 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. 

    Courses offered

    Offer period Offer type Profile Education Semester

    Studieforløb

    Profile Education Semester Offer period