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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.
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