Labs

Attendance is mandatory. Laboratory exercises mainly servers to acquire practical experience of the applied AI techniques in the selected robotic tasks.

The aim of the exercise is to apply the topics explained during the lectures in practical deployment in solving selected robotic problems. In the exercises, students shall develop software to control mobile robots using the algorithms and existing implementations and software libraries.

Exercises at glance

#TWeek	Week	Monday (Room No. KN:E-328)	Instructor
#1	39.	23. 09. - Lab01 - Introduction to CoppeliaSim and Open-Loop Robot Locomotion Control	Miloš Prágr
#2	40.	30. 09. - Lab02 - Exteroceptive sensing and Reactive-based Obstacle Avoidance	Miloš Prágr
#3	41.	07. 10. - Lab03 - Grid and Graph-based Path Planning	Jiří Kubík
#4	42.	14. 10. - Lab04 - Mapping	Jiří Kubík
#5	43.	21. 10. - Lab05 - Mobile Robot Exploration	Jáchym Herynek
#6	44.	28. 10. - Independent Czechoslovak State Day
#7	45.	04. 11. - Lab06 - Incremental Path Planning	Jáchym Herynek
#8	46.	11. 11. - Lab07 - Data Collection Path Planning with Remote Sensing (TSPN)	Jáchym Herynek
#9	47.	18. 11. - Lab08 - Curvature-constrained Data Collection Path Planning (DTSPN)	Jáchym Herynek
#10	48.	25. 11. - Lab09 - Randomized Sampling-based Algorithms	Jáchym Herynek
#11	49.	02. 12. - Lab10 - Curvature-constrained Local Planning with RRT-based algorithms	Jakub Sláma
#12	50.	09. 12. - Lab11 - Risk-aware Planning	Jakub Sláma
#13	51.	16. 12. - Lab12 - Reinforcement Learning with an Inchworm Robot	Jiří Kubík
	52.	23. 12. - Winter holidays (23.12. - 5.1.)
	01.	30. 12. - Winter holidays (23.12. - 5.1.)
#14	02.	06. 01. - Lab13 - Semetral Project Discussion	Miloš Prágr
11. 01. @ 23:59 PST - Ungraded Assessment Deadline!