Camera-based full environmental awareness for automated driving

While traditionally robotic systems such as self-driving cars have been largely relying on Laser or Lidar to actively sense their environment and perform self-localization and mapping (SLAM), camera-based SLAM and odometry algorithms will further increase in performance and importance.

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Tender Information

  • State of the art study, latest trends in SLAM for automated driving applications
  • Development of novel SLAM algorithm and sensor fusion approaches (GPS and IMU sensors) to increase point cloud quality
  • New point cloud post-processing techniques (including machine learning approaches)
  • Investigations on scene understanding using multi-camera systems
  • Control systems theory and control systems engineering
  • Development of a visual SLAM system for real-time mapping of the environment with correct scale
  • Fault-tolerant, fail-operational, and real-time operation

In the proposal for PhD funding, scientific institutions describe:

  • The scientific ability and (if necessary) the required infrastructure to scientifically guide and supervise the PhD candidate
  • The research plan and the focus for the advertised thesis
  • The publication and dissemination plan
  • The teaching plan (courses, trainings, etc.) for the doctoral studies
  • Planned supporting master’s and bachelor theses
  • Total costs of the PhD thesis as well as requested total amount of financial contribution from VIRTUAL VEHICLE (note: adequacy of costs is a major decision criterion)
  • The application comprises the scientific CV of the PhD candidate and the supervising professor at the scientific institution


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