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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.

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


  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


  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

  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

courses/b4m36uir/lectures/start.txt · Last modified: 2020/01/13 23:43 by krajnt1