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-331)
#1	39.	21.09. - Lab01 - Introduction to CoppeliaSim and Open-Loop Robot Locomotion Control
#2	40.	28.09. - National holidays (28.09.)
#3	41.	05.10. - Lab02 - Exteroceptive sensing, Mapping and Reactive-based Obstacle Avoidance
#4	42.	12.10. - Lab03 - Grid and Graph-based Path Planning
#5	43.	19.10. - Lab04 - Incremental Path Planning
#6	44.	26.10. - Lab05 - Mobile Robot Exploration
#7	45.	02.11. - Lab06 - Multi-Robot Exploration
#8	46.	09.11. - Lab07 - Multi-goal Planning, Data Collection Path Planning
#9	47.	16.11. - Lab08 - Curvature-constrained Data Collection Path Planning ((D)TSPN)
#10	48.	23.11. - Lab09 - Randomized Sampling-based Algorithms
#11	49.	30.11. - Lab10 - Asymptotically Optimal Randomized Sampling-based Algorithms
#12	50.	07.12. - Lab11 - Game Theory in Robotics - Patrolling, Greedy Policy
#13	51.	14.12. - Lab12 - Game Theory in Robotics - MCTS Policy, Value Iteration Policy
	52.	21.12. - Winter holidays (21.12. - 3.1.)
	53.	28.12. - Winter holidays (21.12. - 3.1.)
#14	01.	04.01. - Lab13 - Game Theory in Robotics - Algorithms from GT, e.g. Double Oracle, Gap Edges, ...
TBA - Ungraded Assessment Deadline!