151-0634-00L  Perception and Learning for Robotics

SemesterFrühjahrssemester 2020
DozierendeC. D. Cadena Lerma, J. J. Chung
Periodizitäteinmalige Veranstaltung
LehrspracheEnglisch
KommentarNumber of participants limited to: 30

To apply for the course please create a CV in pdf of max. 2 pages, including your machine learning and/or robotics experience. Please send the pdf to cesarc@ethz.ch for approval.



Lehrveranstaltungen

NummerTitelUmfangDozierende
151-0634-00 APerception and Learning for Robotics
The lectures take place on the following days in the 2nd week of the Semester:

- Monday 24.02.2020 at 14-18
- Wednesday 26.02.2020 at 14-18
- Friday 28.02.2020 at 14-18

The venue will be announced later.
120s Std.
24.02.14-18LEE C 114 »
26.02.14-18HG F 26.3 »
28.02.14-18LEE C 114 »
C. D. Cadena Lerma, J. J. Chung

Katalogdaten

KurzbeschreibungThis course covers tools from statistics and machine learning enabling the participants to deploy these algorithms as building blocks for perception pipelines on robotic tasks. All mathematical methods provided within the course will be discussed in context of and motivated by example applications mostly from robotics. The main focus of this course are student projects on robotics.
LernzielApplying Machine Learning methods for solving real-world robotics problems.
InhaltDeep Learning for Perception; (Deep) Reinforcement Learning; Graph-Based Simultaneous Localization and Mapping
SkriptSlides will be made available to the students.
LiteraturWill be announced in the first lecture.
Voraussetzungen / BesonderesThe students are expected to be familiar with material of the "Recursive Estimation" and the "Introduction to Machine Learning" lectures. Particularly understanding of basic machine learning concepts, stochastic gradient descent for neural networks, reinforcement learning basics, and knowledge of Bayesian Filtering are required. Furtheremore, good knowledge of programming in C++ and Python is required.

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte4 KP
PrüfendeC. D. Cadena Lerma, J. J. Chung
Formbenotete Semesterleistung
PrüfungsspracheEnglisch
RepetitionRepetition nur nach erneuter Belegung der Lerneinheit möglich.
Zusatzinformation zum PrüfungsmodusThe grade is based on the realization of a project, presentation and demo (50%), the project report (40%) and quizzes during the lecture block (10%).

Lernmaterialien

Keine öffentlichen Lernmaterialien verfügbar.
Es werden nur die öffentlichen Lernmaterialien aufgeführt.

Gruppen

Keine Informationen zu Gruppen vorhanden.

Einschränkungen

PlätzePlätze beschränkt. Spezielles Auswahlverfahren.
WartelisteBis 21.02.2020
BelegungsendeBelegung nur bis 09.02.2020 möglich

Angeboten in

StudiengangBereichTyp
Maschineningenieurwissenschaften MasterRobotics, Systems and ControlWInformation
Robotics, Systems and Control MasterKernfächerWInformation