[ 993TAMR19 ] Subject AI and Mechatronics – Robotics and Autonomous Systems

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.
Subordinated subjects, modules and lectures