Autonomous Systems and Robotics

The University of Klagenfurt offers high-quality academic education in Autonomous Systems and Robotics with graduates finding great jobs in automotive and aerospace, robotics, transport, engineering offices, and consulting.

Which courses are offered?

Compulsory LECTURES

  • Robotics (Kyandoghere Kyamakya): Overview, applications; mathematics; mechanical design; sensors and actuators; direct kinematics; inverse kinematics; work space analysis and trajectory planning; robot control; AI reasoning; probabilistic robotics; task planning; robot vision.

  • Sensors and Actuators (Hubert Zangl): Pneumatic and hydraulic actuators; electric motors, linear actuators;  nonmechanical actuators; proprioception; exteroception, pressure and compass sensors; beacon-based sensing, time of flight camera, laser range finder, radar; smart sensors and actuators, energy management, energy harvesting, energy storage.

  • Control of Autonomous Systems (Stephan Weiss): Kinematic and dynamic modeling of common mobile robotic systems, including legged, wheeled, and aerial robots; practical understanding of modeling these systems and to build a solid foundation in kinematics, dynamics, and multi-body rotations; essential tools for the design and control of mobile robotic systems.

Advanced LECTURES

  • Measurements Signal Processing (Harald Gietler): Estimation and detection theory with a focus on applications in resource efficient sensors for autonomous systems and robotics.

  • Robust Design and Reliability (Hubert Zangl): Probabilistic modeling of failures; failure mechanisms; functional safety, hazard analysis and risk assessment; fault tree analysis; reliability block diagram; failure mode and effect analysis; fault injection; experimental design; analysis of variance; optimal design of sensors, actuators, and sensor electronics given uncertain parameters and noise.

  • CAE of Mechatronics Systems (Hubert Zangl): Electrical and mechanical properties of materials and mathematical modeling; multi-physical simulation of thermal, capacitive, piezoelectric, piezoresistive, electrostrictive, thermal and magnetic sensors and/or actuators.

  • Vision Based State Estimation and Sensor Fusion (Stephan Weiss): Sensor modeling and uncertainty; camera models and 6DoF pose estimation; barometer/GPS/IMU models; nonlinear state estimation and filtering (Kalman, EKF, UKF); sensor fusion and bundle adjustment; observability analysis; SLAM/VIO basics.

  • Neurocomputing in Robotics and Intelligent Transportation (Fadi Al Machot): Object segmentation; object Recognition; object tracking; face recognition; image stitching; video understanding; event detection; sensor fusion.