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
ECTS value
5
Internal Course Code
Responsible study board
Administrative Unit
Date of Approval
Course Responsible
| Name | 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 | Department | City | |
|---|---|---|---|
| Kirsten Thorup Nielsen | kitho@tek.sdu.dk | TEK Studieadministration, Det Tekniske Fakultet |
Offered in
Level
Offered in
Duration
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
Number of lessons
Teaching Method
Instruction
Teaching language
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