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


Course Title

Bio-inspired Autonomous Systems

ECTS value


Internal Course Code


Responsible study board

Academic Study Board of the Faculty of Engineering

Administrative Unit

Mærsk McKinney Møller Instituttet

Date of Approval


Course Responsible

Name Email Department
Dirk Kraft Mærsk Mc-Kinney Møller Instituttet
Kristian Severin Rasmussen TEK Uddannelse, Det Tekniske Fakultet

Programme Secretary

Name Email Department City
Kirsten Thorup Nielsen TEK Studieadministration, Det Tekniske Fakultet

Offered in




Offered in



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 


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


Number of lessons

48 hours per semester

Teaching language


Examination regulations

Exam regulations


Exam regulations

Examination is held

In the end of the semester. 








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


Second examiner: Internal


7-point grading scale


Student Identification Card - Exam number



ECTS value


Courses offered

Offer period Offer type Profile Education Semester


Profile Education Semester Offer period