Cesar Dario Cadena Lerma: Catalogue data in Spring Semester 2020

Name Dr. Cesar Dario Cadena Lerma
Name variantsCesar Cadena
Cesar Cadena Lerma
Cesar Dario Cadena
Cesar Dario Cadena Lerma
Address
Autonome Systeme
ETH Zürich, LEE J 201
Leonhardstrasse 21
8092 Zürich
SWITZERLAND
Telephone+41 44 633 88 03
E-mailcesarc@ethz.ch
URLhttps://n.ethz.ch/~cesarc/
DepartmentMechanical and Process Engineering
RelationshipLecturer

NumberTitleECTSHoursLecturers
151-0634-00LPerception and Learning for Robotics Restricted registration - show details
Number 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.
4 credits9AC. D. Cadena Lerma, J. J. Chung
AbstractThis 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.
ObjectiveApplying Machine Learning methods for solving real-world robotics problems.
ContentDeep Learning for Perception; (Deep) Reinforcement Learning; Graph-Based Simultaneous Localization and Mapping
Lecture notesSlides will be made available to the students.
LiteratureWill be announced in the first lecture.
Prerequisites / NoticeThe 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.