Table of Contents

Lectures

Supporting materials for the lectures of the academic year 2022/2023. 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 for your own notes from the lectures. They are rather provided to help you to understand the studied problems.

#TWeek Week Monday (Room No. KN:E-107) 11:00-12:30
#1 38. Lecture 01 - Course information, introduction to robotics 19.09. - lec01
#2 39. Lecture 02 - Robotic paradigms and control architectures 26.09. - lec02
#3 40. Lecture 03 - Path planning - grid and graph-based path planning methods 03.10. - lec03
#4 41. Lecture 04 - Robotic information gathering - Mobile robot exploration 10.10. - lec04
#5 42. Lecture 05 - Multi-goal path planning 17.10. - lec05
#6 43. Lecture 06 - Data collection planning 24.10. - lec06
#7 44. Lecture 07 - Curvature-constrained data collection planning 31.10. - lec07
#8 45. Lecture 08 - Randomized sampling-based motion planning methods 07.11. - lec08
#9 46. Lecture 09 - Pursuit-evasion games I 14.11. - lec09
#10 47. Lecture 10 - Pursuit-evasion games II 21.11. - lec10
#11 48. Lecture 11 - Temporal task-motion planning 28.11. - lec11
#12 49. Selected topic – Autonomous exploration and search missions in underground environments (tentative topic) 05.12. - lec12
#13 50. Selected topics – Locomotion Control and Environment Interactions Handling for Multi-legged Walking Robots and Combining Continuous and Combinatorial Optimization for Multi-goal Trajectory Planning 12.12.
51. Winter holidays (19.12. - 8.1.) 19.12.
52. Winter holidays (19.12. - 8.1.) 26.12.
01. Winter holidays (19.12. - 8.1.) 02.01.
#14 02. Exam Test (reserve) 09.01.
14.1.2023 @ 23.59 PST - Ungraded Assessment Deadline!

1. Course information, introduction to robotics

— Jan Faigl 2022/09/25 21:51

2. Robotic paradigms and control architectures

— Jan Faigl 2022/09/26 08:08

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

— Jan Faigl 2022/10/02 21:29

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 2022/10/09 22:05

5. Multi-goal path planning

— Jan Faigl 2022/10/16 23:05

6. Data collection planning

— Jan Faigl 2022/10/21 18:22

7. Curvature-constrained data collection planning

— Jan Faigl 2022/10/30 21:12

8. Randomized sampling-based motion planning methods

— Jan Faigl 2022/11/06 12:11

9. Pursuit-evasion games I

— Tomas Kroupa 2022/11/14 10:24

10. Pursuit-evasion games II

— Tomas Kroupa 2022/11/21 09:28

11. Temporal task-motion planning

12. Autonomous Navigation with Environment Changes Understanding

Tomáš Krajník TBD

Topics of Invited Talks

13.A Locomotion Control and Environment Interactions Handling for Multi-legged Walking Robots

Petr Čížek slides

13.B Combining Continuous and Combinatorial Optimization for Multi-goal Trajectory Planning

Petr Váňa

AA. 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

BB. 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

CC. 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

DD. Multi-robot systems

— Jan Faigl 2021/01/03 21:05