author = {D. W\"{u}bben and A. K\"{o}nsgen and A. Udugama and A. Dekorsy and A. F\"{o}rster},
  year = {2020},
  month = {Jan},
  title = {Challenges and Opportunities in Communications for Autonomous Underwater Vehicles},
  series = {Intelligent Systems, Control and Automation: Science and Engineering},
  editor = {F. Kirchner, S. Straube, D. K\"{u}hn, N. Hoyer},
  publisher = {Springer},
  ISBN = {978-3-030-30683-0},
  URL = {https://www.springer.com/gp/book/9783030306823},
  abstract={Wireless communication is essential for autonomous underwater vehicles (AUVs) in order to provide job instructions, forward sensed data or coordinate multiple AUVs working in a swarm. However, communication in the underwater environment is unreliable and does not allow high data rates due to high interference and poor signal propagation conditions. This article reviews existing concepts for underwater communications both from the information transfer as well as from the networking aspect. Introducing semantic communication helps to reduce the amount of transferred data by making use of semantic side information. Opportunistic networks allow end-to-end data forwarding without permanent connectivity and can be extended to make use of the most suitable communication technology when forwarding data with given size and priority. Machine Learning (ML) helps to remember and classify background information to enhance the efficiency of the communication.},
  booktitle={AI Technology for Underwater Robots}