Loading
0000002122 21S 6SWS PR Masterpraktikum - Development of Biologically-inspired Methods for Autonomous Driving (IN2106,IN0012)   Hilfe Logo

LV - Detailansicht

Wichtigste Meldungen anzeigenMeldungsfenster schließen
Allgemeine Angaben
Masterpraktikum - Development of Biologically-inspired Methods for Autonomous Driving (IN2106,IN0012) 
0000002122
practical training
6
Summer semester 2021
... alle LV-Personen
Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems (Prof. Knoll)
(Contact information)
Details
Allocations: 1 
Angaben zur Abhaltung
Autonomous driving, referring to self-driving vehicles or autonomous transport systems, is a hot issue that involves many complex technology fields including sensor technology, control systems, and action planning. Biologically inspired computing is a field of study which seeks to solve computer science problems using models of biology.
In this course, we will focus on solving perception and navigation problems for autonomous driving with biologically-inspired methods. Starting from some conventional algorithms in autonomous driving, we will seek to apply biological models and methods in the progress to develop cognitive algorithms.
Student participants will be arranged into small groups and assigned projects to work throughout the semester.

If you are interested in this course, please send an email briefly describing your research interests to zhuang(at)in.tum.de. Please also include your cv and transcript.
Prerequisites:
- Knowledge of object-oriented programming, C/C++, Python
- Familiarity with Linux (Ubuntu)

Beneficial Knowledge:
- Knowledge and experience with ROS development and simulation
- Machine learning, neural networks
English

work in groups
Details
Für die Anmeldung zur Teilnahme müssen Sie sich in TUMonline als Studierende*r identifizieren.
Note: Please apply via TUM matching system https://matching.in.tum.de/
Zusatzinformationen
Online information
e-learning course (moodle)
Please apply via TUM matching system https://matching.in.tum.de/