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Introduction to Mobile Robotics

This course will introduce basic concepts and techniques used within the field of mobile robotics. We analyze the fundamental challenges for autonomous intelligent systems and present the state of the art solutions. Among other topics, we will discuss kinematics, sensors, vehicle localization, map building, SLAM, and path planning.



Time: Monday, 10:00 c.t. – 12:00
First meeting on April 25, 2022.
Location: This course will be held in a hybrid format. Weekly flipped classroom sessions will be held in-person at Building 101, SR 00-010/14 and via Zoom. See ILIAS for Zoom meeting password.
Learning Platform: ILIAS
Remarks: Due to the Covid-19 crisis, the lecture will be offered in a hybrid format. Those in Freiburg can attend the flipped classroom and exercise sessions in-person and those who are out of town can attend via Zoom. Video lectures and exercises will be uploaded to ILIAS one week before the day of the lecture. Please watch the lecture and start working on the exercises. You may post questions on the lecture by inserting comments in the video page or post questions about the exercises in the forum. We will then have a Q&A; session in the week of the lecture where all the questions will be discussed.

Course Overview

The course will be taught in english and will follow a flipped classroom approach.

Every week there will be:
- a video lecture
- an exercise sheet
- a flipped classroom session (hybrid format - in-person/via zoom, Monday, 10:00 c.t. – 12:00)
- a exercise session (hybrid format - in-person/via zoom, Wednesday, 12:00 c.t. – 14:00, Building 101, SR 00-010/14)

The exam is WRITTEN for most students, except for bachelor students of computer science with Prüfungsordnung 2012.

All learning material including video lectures, slides, and exercises can be found on ILIAS


The course will be taught in english and will follow a flipped classroom approach.

Lecture Dates Topic
00 25-04-2022 Introduction
01 02-05-2022 Linear Algebra
02 09-05-2022 Robot Control Paradigms
03 09-05-2022 Wheeled Locomotion
04 09-05-2022 Proximity Sensors
05 16-05-2022 Probabilistic Robotics
06 23-05-2022 Probabilistic Motion Models
07 30-05-2022 Probabilistic Sensor Models
08 13-06-2022 Bayes Filter - Discrete Filters
09 13-06-2022 Bayes Filter - Particle Filter and MCL
10 20-06-2022 Bayes Filter - Kalman Filter
11 20-06-2022 Bayes Filter - Extended Kalman Filter
12 27-06-2022 Grid Maps and Mapping With Known Poses
13 04-07-2022 SLAM - Simultaneous Localization and Mapping
14 04-07-2022 SLAM - Landmark-based FastSLAM
15 11-07-2022 SLAM - Grid-based FastSLAM
16 11-07-2022 SLAM - Graph-based SLAM
17 18-07-2022 Techniques for 3D Mapping
18 18-07-2022 Iterative Closest Point Algorithm
19 25-07-2022 Path and Motion Planning
20 01-08-2022 Multi-Robot Exploration
21 01-08-2022 Information Driven Exploration
22 01-08-2022 Summary


Each exercise session consists of two parts: answering open questions on the lecture and the discussion of the exercise sheets.

Solving the exercise sheets is recommended but not mandatory to be admitted to the final exam. There are no bonus points.

Exercise sheets will be published one week before the discussion session. We strongly encourage you to solve the exercise sheets beforehand to benefit from the discussions in class.


If you have a question, please post it in the ILIAS forum (so everyone can benefit from the answer). Alternatively, you can also email