Table of Contents

Lectures

Supporting materials for the lectures of the academic year 2018/2019. The materials are slides, also available in printer safe version as handouts with 2×2 and 3×3 slides on a single page.

These supportive materials are not intended as a replacement of your own notes from the lectures. They are rather provided to help you to understand the studied problems.

#TWeek Week Topic Monday
9:15-10:45
KN:E-126
01 39. Lecture 01 - Course information, introduction to robotics 23.09. - lec01
02 40. Lecture 02 - Robotic paradigms and control architectures 30.09. - lec02
03 41. Lecture 03 - Path planning grid and graph-based path planning methods 07.10. - lec03
04 42. Lecture 04 - Robotic information gathering - Mobile robot exploration 14.10. - lec04
05 43. Lecture 05 - Multi-goal planning - Robotic variants of the routing problems 21.10. - lec05
06 44. Public holidays (28.10.)
07 44. Lecture 06 - Data collection planning with curvature-constrained vehicles 04.11. - lec06
08 45. Lecture 07 - Randomized sampling-based motion planning methods 11.11. - lec07
09 46. Lecture 08 - Game theory in robotics 18.11. - lec08
10 47. Lecture 09 - Visibility based pursuit evasion games 25.11. - lec09
11 48. Lecture 10 - Patrolling games 02.12. - lec10
12 49. Lecture 11 - Autonomous navigation 09.12. - lec11
13 50. Lecture 12 - Localisation and mapping 16.12. - lec12
– 52. Winter holidays
– 01. Winter holidays
14 02. Lecture 13 - Long-term navigation and spatio-temporal mapping 06.01. - lec13

1. Course information, introduction to robotics

— Jan Faigl 2019/09/23 09:00

2. Robotic paradigms and control architectures

— Jan Faigl 2019/09/30 09:00

3. Path planning - Grid and graph-based path planning methods

— Jan Faigl 2019/09/27 17:45

4. Robotic information gathering - Mobile robot exploration

— Jan Faigl 2019/10/14 13:50 Update: Comments on Hungarian algorithm and dummy tasks and resources. Further comments on the relation of the decision-making and particular realization of the whole navigation stack.

— Jan Faigl 2019/10/14 08:59

5. Multi-goal (data collection) planning

— Jan Faigl 2019/09/27 17:45

6. Data collection planning with curvature-constrained vehicles

— Jan Faigl 2019/11/04 08:17

7. Randomized sampling-based motion planning methods

— Jan Faigl 2019/11/11 20:31

8. Game theory in robotics

Game theory basics
Pursuit evasion games

— Jan Faigl 2019/09/27 23:06

9. Visibility based pursuit evasion games

— Jan Faigl 2019/09/27 22:59

10. Patrolling games

— Jan Faigl 2019/09/27 22:59

11. Autonomous navigation

Slides
References
  1. Bonin-Font, Francisco, Alberto Ortiz, and Gabriel Oliver. Visual navigation for mobile robots: A survey. Journal of intelligent and robotic systems 53.3 (2008): 263-296. pdf
  2. Rodney Brooks. Intelligence without representation. Artificial Intelligence 91 pdf
  3. Filliat, David, and Jean-Arcady Meyer. Map-based navigation in mobile robots:: I. a review of localization strategies. Cognitive Systems Research 4.4 (2003): 243-282. pdf
  4. Tomáš Krajník, Filip Majer et al. Navigation without localisation: reliable teach and repeat based on the convergence theorem. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018. pdf

12. Simultanneous Localisation and Mapping

Slides
References
  1. Stachniss, Cyrill: Introduction to Robot Mapping video
  2. Cadena et al.: Past, Present and Future of SLAM: Towards the Robust-Perception Age. IEEE T-RO 2018. pdf
  3. Grissetti et al.: Tutorial on Graph-Based SLAM. ITS Magazine pdf

13. Long-term navigation and spatio-temporal mapping

Slides
References
  1. Krajnik et al. CHRONOROBOTICS: Representing the structure of time for service robots In IJCRAI 2019. pdf
  2. Kunze et al. Artificial Intelligence for Long-term Autonomy: a survey. IEEE RA-L 19. pdf
  3. Krajnik et al. Image Features for Visual T\&R Navigation in Changing Environments. RASS 17. pdf
  4. Halodova et al. Predictive and adaptive maps for long-term visual navigation. In IROS 19. pdf
  5. Krajnik et al. FreMEn: Frequency map enhancement for long-term mobile robot autonomy in changing environments.IEEE T-RO 2017. pdf
  6. Krajnik et al. Warped Hypertime Representations for Long-termAutonomy of Mobile Robots IEEE RA-L 2019.pdf

— Tomáš Krajník 2020/01/13 13:28