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:

• Sensors,
• Kinematics,
• Path planning,
• Vehicle localization,
Map building,
• SLAM,
• Exploration of unknown terrain

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• Lecturers: Prof. Dr. Wolfram Burgard
• Co-organizers: Patrick Pfaff, Oscar Martinez Mozos, Dr. Kai O. Arras, Axel Rottmann
• Wednesday 09-11, Thursday 11-12, Room: SR 01-018, Building 101
• Classes / exercises: Thursday 12-13, Room: SR 01-018, Building 101
• Exams: October 6, 2006. (Oral exams, about 20 minutes long).
  For other exam dates, write an email to Prof. Dr. Wolfram Burgard

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Slides

1. Introduction (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
2. Wheeled Locomotion (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
3. Proximity sensors (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
4. Probabilistic Robotics (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
5. Probabilistic Motion Models (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
6. Probabilistic Sensor Models (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
7. Bayes Filter Implementations (Gaussian Filters) (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
8. Bayes Filter Implementations (Discrete Filters) (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
9. Bayes Filter Implementations (Particle Filters) (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
• Additional notes on Particle Filters (PS, PDF).
10. Mapping with known poses (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
• Additional notes on mapping with known poses (PS,PDF).
11. Iterative Closest Point Algorithm (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
12. Line Extraction and First-Order Error Propagation (PDF: 4 on 1)
13. SLAM Mapping (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
14. Landmark-based FastSLAM (PDF: 4 on 1)
15. Grid-based FastSLAM (PDF: 4 on 1)
16. Information Gain-Based Exploration Using Rao-Blackwellized Particle Filters
    (PS, PDF, PS: 4 on 1, PDF: 4 on 1)
• Original paper (PDF)
17. Path Planning and Collision Avoidance (PS, PDF, PS: 4 on 1, PDF: 4 on 1)

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Exercises

1. Exercise sheet 1 (PS, PDF)
2. Exercise sheet 2 (PS, PDF)
3. Exercise sheet 3 (PS, PDF)
4. Exercise sheet 4 (PS, PDF)
5. Exercise sheet 5 (PS, PDF)
• DiscreteFilter.java (Java template for exercise 2)
• input.txt
• input2.txt
6. Exercise sheet 6 (PS, PDF)
NOTE: there is no assignment for 21.06.2006.
7. Exercise sheet 7 (PDF)
8. Exercise sheet 8 (PDF)
9. Exercise sheet 9 (PDF)
10. Exercise sheet 10 (PS, PDF)
11. Exercise sheet 11 (PS, PDF)