Laboratory Exercises

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-307)	Instructor
#1	38.	20.09. - Lab01 - Introduction to CoppeliaSim and Open-Loop Robot Locomotion Control	Jiří Kubík
#3	39.	27.09. - Lab02 - Exteroceptive sensing and Reactive-based Obstacle Avoidance	Jiří Kubík
#3	40.	04.10. - Lab03 - Mapping	David Valouch
#4	41.	11.10. - Lab04 - Grid and Graph-based Path Planning	David Valouch
#5	42.	18.10. - Lab05 - Incremental Path Planning	David Valouch
#6	43.	25.10. - Lab06 - Mobile Robot Exploration	Miloš Prágr
#7	44.	01.11. - Lab07 - Semestral Project Assignment	Miloš Prágr
#8	45.	08.11. - Lab08 - Data Collection Path Planning with Remote Sensing (TSPN)	Jindřiška Deckerová
#9	46.	15.11. - Lab09 - Curvature-constrained Data Collection Path Planning (DTSPN)	Jakub Sláma
#10	47.	22.11. - Lab10 - Randomized Sampling-based Algorithms	Jakub Sláma
#11	48.	29.11. - Lab11 - Curvature-constrained Local Planning with RRT-based algorithms	Jakub Sláma
#12	49.	06.12. - TBD - Reading group
#13	50.	13.12. - TBD - Reading group
	51.	20.12. - Winter holidays (20.12. - 2.1.)
	52.	27.12. - Winter holidays (20.12. - 2.1.)
#14	01.	03.01. - Lab14 - Semetral Project Discussion	Miloš Prágr/Petr Čížek
08.01. @ 23:59 CET - Ungraded Assessment Deadline!