Mobile Robotics

Lecture (2h) and Exercise (2h) (5 ECTS)

Mobile robots have been sent to Mars, can vacuum clean our homes, mow the lawn, and are promised to carry us around in the form of self-driving cars or even flying taxis. In this module, you will learn about the different component of such mobile robots and their interactions: from perception to estimation, mapping, and control. As will also learn to work with different mathematical representations of robot states and maps. Since deployment in open-ended environments requires sophisticated perception, localisation, and mapping approaches, we will dedicate a substantial part of the course towards probabilistic multi-sensor-fusion and modern Simultaneous Localisation and Mapping (SLAM) and more general Spatial AI systems – including elements of Machine Learning. In the last part, you will then be learning about how to use these representations of robot state and surroundings for navigation and control.

Contents

I Foundations:

II Multi-Sensor Estimation:

III From SLAM to Spatial AI:

IV Planning and Control:

Prerequisites

Passion for mobile robots and drones, as well as solid mathematical foundations regarding analysis, linear algebra, and probability theory. In parallel to this course, “Mobile Robotics Practicals” is offered, the participation in which is highly recommended. Additionally, participation in the following courses is highly recommended:

The exercises will require solid knowledge of Python.

Literature

General