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

Academic Study Board of the Faculty of Engineering

Teaching language: English
EKA: T930009102
Censorship: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Summer school (spring)
Level: Bachelor

Course ID: T930009101
ECTS value: 5

Date of Approval: 08-12-2020


Duration: Intensive course

Version: Archive

Course ID

T930009101

Course Title

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

ECTS value

5

Internal Course Code

XSR-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 , Den Tekniske Fakultetsadministration
Preben Hagh Strunge Holm prebenh@mmmi.sdu.dk Mærsk Mc-Kinney Møller Instituttet, SDU Robotics

Programme Secretary

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

Offered in

Odense

Level

Bachelor

Offered in

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 MySchedule

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

T930009102

Name

Exam

Description

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

Form of examination

Oral exam

Censorship

Second examiner: Internal

Grading

7-point grading scale

Identification

Student Identification Card - Date of birth

Language

English

ECTS value

5

Additional information

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

  1. Undergraduate and graduate students from partner universities (exchange); international undergraduate and graduate guest students (fee-paying); undergraduate and graduate students from other Danish universities. 
  2. Ph.D students from partner universities and other international Ph.D. students; other applicants. 

Students are prioritised on a first come, first served basis, i.e. according to the time we receive your complete application. 

In case a course is filled up, we try to offer you an alternative course from your list of priorities. All final decisions about admission will be sent out continually.  

Courses offered

Period Offer type Profile Programme Semester

Studieforløb

Profile Programme Semester Period