Xiao Wang is a research assistant and PhD student in the Cyber-Physical Systems Group under Prof. Dr.-Ing. Matthias Althoff since 2019. She graduated with the Master of Science degree in Mechanical Engineering from the Technische Universität München, Germany, in 2018. She received the Bachelor of Engineering degree in Vehicle Engineering from Tongji University, Shanghai, China.
Her research focuses on motion planning for autonomous vehicles, formal methods, and safe reinforcement learning.
Currently, there are no specific open topics. If you are interested in her research and want to write a thesis in this area, please feel free to contact her. General ideas could be to apply formal method to standard RL techniques to increase safety, to benchmark state-of-art safe RL algorithms, to learn driving behaviors from real traffic data, or to increase sample efficiency of RL for motion planning, etc.
- BT: Christoph Pillmayer - "Online Verification for Autonomous Vehicles using Motion Primitives and Deep Reinforcement Learning" (finished in SS19)
- BT: Hagen Winkelmann - "Learning Cost Functions for Sampling Based Planners in Autonomous Driving" (finished in SS19)
- MT: Hanna Krasowski - "Safe Reinforcement Learning for Autonomous Vehicles (finished in WS19)"
Task: Integrate our planning algorithms in Baidu Apollo Autonomous Driving platform
- Python programming
- C++ programming
- ROS experience
- (Optional) Docker and Bazel experience is a plus
- Seminar: Cyber-Physical Systems
- Master Practical Course: Motion Planning for Autonomous Vehicles
- Exercise: Techniques in Artificial Intelligence