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34792 Ph.d.-kursus - Videregående Emner i Perception for Robotter og Autonome Systemer

2025/2026

Kursusinformation
PhD Course - Advanced topics in Perception for Robotics and Autonomous Systems
Engelsk
5
Ph.d., Fagligt fokuseret kursus
Forår og Juni
Kurset indeholder også sommer 3 ugers perioden
Campus Lyngby
The course consists of two parts. The first part is a reading club, where participants attend and discuss state-of-the-art or seminal papers, after a short presentation. The second part consists of preparing and handing in a short report where participants, either individually or in small groups, showcase their own research building on top of concepts covered or inspired by the course.
13-uger + 3-uger
Aftales med underviser, Aftales med underviser
Bedømmelse af opgave(r)/rapport(er)
Skriftlige hjælpemidler er tilladt
bestået/ikke bestået , intern bedømmelse
31389
31389
34756/31388
Minimum 2 Maksimum: 12
Lazaros Nalpantidis , Lyngby Campus, Bygning 326 , lanalpa@dtu.dk
34 Institut for Elektroteknologi og Fotonik
I studieplanlæggeren
Kontakt underviseren for information om hvorvidt dette kursus giver den studerende mulighed for at lave eller forberede et projekt som kan deltage i DTUs studenterkonference om bæredygtighed, klimateknologi og miljø (GRØN DYST). Se mere på http://www.groendyst.dtu.dk
Overordnede kursusmål
To make participants able to identify and comprehend state-of-the-art research in perception for robotics and autonomous Systems
The course aims to give participants the ability to showcase their own research building on top of advanced topics in perception for robotics and autonomous systems covered in this course.
Læringsmål
En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:
  • Robust Machine Learning
  • Autonomous Robot Perception
  • Label-Efficient Learning
  • Meta-learning
  • Unsupervised learning for Autonomous Systems
  • Few-shot learning
  • Domain adaptation
  • Multi-task learning
Kursusindhold
Advanced topics in robots and autonomous systems, including: Robust Machine Learning for Autonomous Robot Perception, Unsupervised learning for Autonomous Systems, Label-Efficient Learning, Meta-learning.
Participants work individually or in small groups on an assignment building on a concept covered or inspired by the course. The topic will be chosen by the participants and approved by the lecturers.
Litteraturhenvisninger
Selected state-of-the-art and seminal papers.
Sidst opdateret
02. maj, 2025