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Environment perception for autonomous driving applications

Master Project/Master Thesis (Ref.Nr.E_078)

Autonomous driving is an important future topic in the automotive industry. Environment perception is one of the biggest challenges for fully autonomous driving. Various sensors have different advantages and disadvantages in certain operational ranges and situations. Using multiple different sensors enables exploiting advantages of all, but it introduces the problem of how to effectivelly handle so much data. Sensor fusion enables to combine readings from many sensors for a single usable information. In this project, the student task is to develop a reliable sensor fusion system, using many state-of-the art sensors such as: ultrasonic, lidar, stereo vision. The Sensor fusion system should provide information about available free space for driving.


Your duties and responsibilities:

  • Setting up a system consisting of multiple state-of-the-art sensors (off the shelf)
  • Identification of individual sensor characteristics
  • Developing a sensor fusion algorithm for occupancy grid mapping
  • Visualization of fused measurement
  • Developing a calibration procedure
  • Implementation on real-time computational unit

What we expect:

  • Study field: Telematics, Electrical Eng., Mathematics, Automotive, Technical Informatics, etc.
  • Knowledge of C++, Matlab or ROS
  • Interest in work with hardware
  • Enthusiasm and engagement
  • Good command of English

What we offer:

  • Technical support in field of “autonomous driving”
  • Work with state-of-the art sensors on hardware prototype.
  • Work in a committed, dynamic team
  • Financial remuneration

Details in pdf Format

For questions about the topic contact:
Zlatan Ajanovic – zlatan.ajanovic@v2c2.at

For more information please contact:
Mag. Raphaela Haring
hr@v2c2.at
Tel.: +43-(0)316-873-9613
www.v2c2.at