Bio-inspired Autonomous Systems

Academic Study Board of the Faculty of Engineering

Teaching language: English
EKA: T550061102
Censorship: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Master

Course ID: T550061101
ECTS value: 5

Date of Approval: 29-04-2020


Duration: 1 semester

Version: Archive

Course ID

T550061101

Course Title

Bio-inspired Autonomous Systems

ECTS value

5

Internal Course Code

RM-BAS

Responsible study board

Academic Study Board of the Faculty of Engineering

Date of Approval

29-04-2020

Course Responsible

Name Email Department
Dirk Kraft kraft@mmmi.sdu.dk Mærsk Mc-Kinney Møller Instituttet
Kristian Severin Rasmussen krsr@tek.sdu.dk TEK Uddannelse, Det Tekniske Fakultet

Programme Secretary

Name Email Department City
Kirsten Thorup Nielsen kitho@tek.sdu.dk TEK Studieadministration, Det Tekniske Fakultet

Offered in

Odense

Level

Master

Offered in

Spring

Duration

1 semester

Recommended prerequisites

It is recommended that the student has followed the 1st semester course in Classical Autonomous Systems and has good knowledge of programming, control theory, robotics, and mathematics. 

Learning objectives - Knowledge

Having completed the course, the successful student will have knowledge about: 
  • The broad, general principles of the field of Embodied AI 
  • Fundamental mechanisms of bio-inspired perception, actuation, control and navigation in the context of autonomous systems 
  • The process through which coordination and other emergent behaviours appear in bio-inspired robot swarms 

Learning objectives - Skills

Having completed the course, the successful student will be able to: 
  • Choose appropriate bio-inspired learning techniques to solve learning problems in autonomous robotic systems 
  • Identify relevant bio-inspired perception, control, navigation, and learning techniques for the design of autonomous robotic systems 
  • Develop and implement bio-inspired methods for perception, control, navigation, and learning in simulated environments 
  • Evaluate and improve bio-inspired techniques applied to autonomous systems 

Learning objectives - Competences

Having completed the course, the successful student will be able to: 
  • Propose solutions to problems and scenarios within the context of autonomous systems for which bio-inspired approaches are appropriate  
  • Design autonomous robotics systems integrating principles of embodied AI and bio-inspiration 

Content

Introduction to bioinspiration and Embodied AI 

Models of animal uni- and multi-sensorial perception  
  • Biological sensing and perception 
  • Motion perception and optical flow 
  • Active perception 
  • Non-visual perception 
  • Multisensory integration 

Bio-inspired actuation and locomotion 
  • Central pattern generators 
  • Legged locomotion and passive-dynamic walking 
  • Snake-robot locomotion 
  • Flapping-wing robots 
  • Soft robotic actuators 

Biological strategies and principles of control and navigation for autonomous systems 
  • Braitenberg vehicles 
  • Path integration models for bio-inspired navigation 
  • Bio-inspired SLAM 

Fundamentals of bio-inspired learning 
  • Biological basis of Reinforcement Learning 
  • Evolutionary robotics 
  • Input Correlation Learning 

Bio-inspired coordination of robot swarms 
  • Self-organization 
  • Collective decision-making 
  • Boids 

URL for Skemaplan

Teaching Method

Instruction

Number of lessons

48 hours per semester

Teaching language

English

Examination regulations

Exam regulations

Name

Exam regulations

Examination is held

In the end of the semester. 

Tests

Exam

EKA

T550061102

Name

Exam

Description

Examination conditions:

The mandatory exercises and the project reports must be handed in on time and in accordance with requirements specified at the beginning of the semester.

Final Exam

Grading is based on an individual oral examination covering the project and the theory presented in the course lectures. The portfolio of group project reports forms the starting point of the exam and will be part of the assesment. 

Form of examination

Oral examination

Censorship

Second examiner: Internal

Grading

7-point grading scale

Identification

Student Identification Card - Exam number

Language

English

ECTS value

5

Courses offered

Offer period Offer type Profile Education Semester

Studieforløb

Profile Education Semester Offer period