Robust and collective perception in highly automated driving
Bachelor’s Thesis, Master’s Thesis, Student Job, Research Project
We are currently looking for motivated students interested in contributing to several research projects in the area of highly automated vehicles including: robustness optimization and evaluation of perception algorithms, environment simulation and cooperative perception.
Highly automated or autonomous vehicles must be able to perceive their surroundings correctly even under difficult weather conditions. Only with a correct and complete knowledge of its environment an autonomous vehicle is able to plan safe manoeuvres without harming its environment. Therefore, algorithms and perceptual systems for local and cooperative perception must be investigated and optimized with respect to their robustness against varying environmental conditions.
Pipeline for robust perception optimization and evaluation
The following list gives an incomplete overview of topics which can be worked on:
- Investigation and improvement of perception algorithms for robustness against environmental conditions
- Fusion algorithms for multi-sensor-fusion and collective perception
- Safety evaluation for perception systems
- Improvement of LiDAR-based object detection
- Realism validation of simulated weather effects on LiDAR sensors
- Implementation and evaluation of tracking/prediction algorithms
- Extension of Simulation Environments
If you are interested in one of the following topics, this job may well be what you are looking for.
- Automated vehicles
- Virtual environments
- Computer vision
- Modelling & investigation of environmental influences
- Object tracking & fusion algorithms
- Sensor modelling
Basic Skills (topic dependent):
Most importantly, you should be interesed in one of the listed topics!