Es ist eine neuere Version 2023W dieses Fachs/Moduls im Curriculum Master's programme Artificial Intelligence 2023W vorhanden.
Workload
Mode of examination
Education level
Study areas
Responsible person
Coordinating university
16,5 ECTS
Accumulative subject examination
M1 - Master's programme 1. year
Computer Science
Sepp Hochreiter
Johannes Kepler University Linz
Detailed information
Original study plan
Master's programme Artificial Intelligence 2019W
Objectives
In this elective track, students learn to apply AI techniques to robotics and autonomous systems. Robotics deals with the construction and operation of robots as well as computer systems for their control, sensory feedback, and information processing. Autonomous systems include self-driving cars, autonomous drones, and production systems that work independent of human control. Robots and other autonomous machines are steered by control techniques such as adaptive optimal control known as reinforcement learning in the field of AI. AI methods concerning the perception and model-building of the environment, planning, and self-localization are crucial for robotics and autonomous systems. These techniques can be complemented by learning a model from data in contrast to classical techniques in mechatronics.
Subject
The contents of this subject result from the contents of its courses.
