Foto von Xiao Wang

Xiao Wang, M.Sc.

Technische Universität München

Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)

Postadresse

Postal:
Boltzmannstr. 3
85748 Garching b. München

Curriculum Vitae

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.

Offered Theses:

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.

Supervised theses:

  • 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)"

Ongoing theses:

  • MT: Xi Chen - "Learning Driving Policies Using Reinforcement Learning Combined with Sampling-based Motion Planner (Submission: 2020.09.17)"
  • MT: Kailiang Dong - "Generative Adversarial Imitation Learning for Highway Autonomous Driving with Safety Guarantees (Submission: 2020.11.05)"
  • MT: Zhenyu Li - "Safe Reinforcement Learning for Continuous Control Tasks (Submission: 2020.12.05)"

Offered Hiwi Job

Apollo Integration:

Task: Integrate our planning algorithms in Baidu Apollo Autonomous Driving platform

Requirements:

  • Python programming
  • C++ programming
  • ROS experience
  • (Optional) Docker and Bazel experience is a plus

Teaching

WS 2020/21

- Exercise: Techniques in Artificial Intelligence

- Practical Course: Motion Planning for Autonomous Vehicles

SS 22

- Seminar: Cyber-Physical Systems

- Practical Course: Motion Planning for Autonomous Vehicles

WS 2019/20

- Exercise: Techniques in Artificial Intelligence

SS 19

- Seminar: Cyber-Physical Systems

- Master Practical Course: Motion Planning for Autonomous Vehicles

WS 2018/19

- Exercise: Techniques in Artificial Intelligence

- Practical Course: Motion Planning for Autonomous Vehicles

Publications

2020

  • Krasowski, Hanna; Wang, Xiao; Althoff, Matthias: Safe Reinforcement Learning for Autonomous Lane Changing Using Set-Based Prediction. 2020 IEEE International Conference on Intelligent Transportation Systems (ITSC), 2020 more… BibTeX Full text (mediaTUM)