Uni-Logo
You are here: Home Teaching SS 2018 Introduction to Mobile Robotics
Artikelaktionen

Introduction to Mobile Robotics - SS 2018

Introduction to Mobile Robotics (engl.) - Autonomous Mobile Systems

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
  • Path planning
  • Exploration of unknown terrain

  • Lecturer: Prof. Dr. Wolfram Burgard,
  • Co-organizers: Chau Do Marina Kollmitz, Lukas Luft
  • Lecture: Wed 16.00-18.00 / Fri 14.00-15.00, Building: 101, Room: SR 00-010/014
  • Exercises: Fri 15.00-16.00, Building: 101, Room: SR 00-010/014
  • Exam: The exam is ORAL for bachelor students of Computer Science and WRITTEN for everyone else.
    1. WRITTEN: Wed 19-09-2018, 10:00, Building: 082 Room: 00-006 (Kinohörsaal)
    2. ORAL: Please check the date in your HISinOne
  • post-exam review: Tue 23-10-2018, 10:00-12:00, Building: 101, Room: SR 01-016

Lectures

Lecture Dates Topic Slides Recordings
00 18-04-2018 Introduction PDF MP4
01 20-04-2018
25-04-2018
Linear Algebra PDF MP4
MP4
02 25-04-2018 Robot Control Paradigms PDF MP4
03 25-04-2018
27-04-2018
Wheeled Locomotion PDF MP4
MP4
04 27-04-2018 Proximity Sensors PDF MP4
05 02-05-2018
02-05-2018
04-05-2018
Probabilistic Robotics PDF MP4
MP4
MP4
06 09-05-2018
09-05-2018
Probabilistic Motion Models PDF MP4
MP4
07 11-05-2018 Probabilistic Sensor Models PDF MP4
MP4
08 18-05-2018 Bayes Filter - Discrete Filters PDF MP4
09 30-05-2018
01-06-2018
Bayes Filter - Particle Filter and MCL PDF MP4
MP4
10 06-06-2018 Bayes Filter - Kalman Filter PDF MP4
11 08-06-2018 Bayes Filter - Extended Kalman Filter PDF MP4
12 13-06-2018
15-06-2018
Grid Maps and Mapping With Known Poses PDF MP4
MP4
13 22-06-2018 SLAM - Simultaneous Localization and Mapping PDF MP4
14 27-06-2018 SLAM - Landmark-based FastSLAM PDF MP4
15 29-06-2018
04-07-2018
SLAM - Grid-based FastSLAM PDF MP4
MP4
16 04-07-2018
06-07-2018
SLAM - Graph-based SLAM PDF MP4
MP4
17 11-07-2018 Techniques for 3D Mapping PDF MP4
18 11-07-2018 Iterative Closest Point Algorithm PDF MP4_ss16
19 13-07-2018
18-07-2018
18-07-2018
Path and Motion Planning PDF MP4_ss16
MP4
MP4
20 20-07-2018 Multi-Robot Exploration PDF MP4
MP4_ss16
21 20-07-2018 Information Driven Exploration PDF MP4_ss16

Exercises

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 on Fridays and will be discussed in class one week later. We strongly encourage you to solve the exercise sheets beforehand to benefit from the discussions in class.

Join this Google group forum for discussing questions on lectures and exercises or send a mail to mobilerobotics@informatik.uni-freiburg.de for an appointment with one of the teaching assistants.

Sheet Due date Topic Exercise Sheet Exercise Material Solutions
01 20-04-2018 Setup Python PDF func.py
02 27-04-2018 Linear Algebra PDF laserscan.dat PDF
03 04-05-2018 Locomotion, Differential Drive PDF PDF
04 11-05-2018 Bayes Rule PDF PDF
05 18-05-2018 Sampling, Motion Models PDF PDF
06 01-06-2018 Sensor Models PDF PDF
07 08-06-2018 Discrete Filter, Particle Filter PDF pf_framework.tar.gz PDF
08 15-06-2018 Extended Kalman Filter PDF kf_framework.tar.gz PDF
09 22-06-2018 Mapping with Known Poses PDF PDF
10 29-06-2018 Simultaneous Localization and Mapping PDF PDF
11 06-07-2018 FastSLAM PDF fastSLAM_framework.tar.gz
fastSLAM_algorithm.pdf
PDF
12 13-07-2018 Iterative Closest Point Algorithm PDF icp_framework.tar.gz PDF
13 20-07-2018 Path Planning PDF planning_framework.tar.gz PDF


Additional Material

  • Notes on one dimensional Gaussians (PDF)
  • Notes on multi dimensional Gaussians (PDF)
  • Python cheat sheet (PDF)
  • Matrix cookbook (PDF)
Benutzerspezifische Werkzeuge