Lectures

Supporting materials for the lectures of the academic year 2021/2022. 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 Lecture
#1 38. 21.09.2021 KN:E-107 @ 11:00-12:30
Lecture 01 - Course information, introduction to robotics
#2 39. 27.09.2021 KN:E-107 @ 11:00-12:30
Lecture 02 - Robotic paradigms and control architectures
#3 40. 04.10.2021 KN:E-107 @ 11:00-12:30
Lecture 03 - Path planning - grid and graph-based path planning methods
#4 41. 11.10.2021 KN:E-107 @ 11:00-12:30
Lecture 04 - Robotic information gathering - Mobile robot exploration
#5 42. 18.10.2021 KN:E-107 @ 11:00-12:30
Lecture 05 - Multi-goal Path planning
#6 43. 25.10.2021 KN:E-107 @ 11:00-12:30
Lecture 06 - Data Collection Planning
#7 44. 01.11.2021 KN:E-107 @ 11:00-12:30
Lecture 07 - Curvature-constrained Data collection Planning
#8 45. 08.11.2021 KN:E-107 @ 11:00-12:30
Lecture 08 - Randomized sampling-based motion planning methods
#9 46. TBS - Sequential decision-making under uncertainty - Markov Decision Processes
#10 47. TBS - Partially Observable Markov Decision Processes (POMDPs)
#11 48. 29.11.2021 KN:E-107 @ 11:00-12:30
Lecture 11 - Temporal Task-Motion Planning
vs. TBS - Reading group: Lifelong planning approaches and real-time heuristic search - D* lite, LRTA*, ARA*
#12 49. 06.12.2021 KN:E-107 @ 11:00-12:30
Lecture 12 - Multi-robot Systems
vs. TBS - Reading group: on-line decision making and adaptive informative path planning
#13 50. TBS - Reading group: Motion planning with uncertainty
51. 21.12. - Winter holidays (21.12. - 3.1.)
52. 28.12. - Winter holidays (21.12. - 3.1.)
#14 01. reserve

1. Course information, introduction to robotics

Jan Faigl 2020/09/18 10:50

2. Robotic paradigms and control architectures

Jan Faigl 2020/09/19 18:34

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

Jan Faigl 2020/10/12 16:19

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 2020/10/19 09:10

5. Multi-goal Path planning

Jan Faigl 2020/10/19 09:10

6. Data Collection Planning

Jan Faigl 2020/10/16 12:46

7. Curvature-constrained Data collection Planning

Jan Faigl 2020/10/19 09:10

8. Randomized sampling-based motion planning methods

Jan Faigl 2020/10/19 09:10

9. Game theory in robotics

Game theory basics
Pursuit evasion games

Pavel Rytir 2020/12/07 19:00

10. Visibility based pursuit evasion games

Pavel Rytir 2020/12/07 19:00

11. Patrolling games

Pavel Rytir 2020/12/07 19:00

12. Temporal Task-Motion Planning

13. Multi-robot Systems

Jan Faigl 2021/01/03 21:05

Topics on Autonomous Navigation, Localization, and Mapping

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

courses/xep36uir/lectures/start.txt · Last modified: 2021/08/24 19:58 by faiglj