Abstract
Navigating autonomously underwater, where a priori information on the environment is sparse and changing ambient conditions complicate perception, requires robust sensing capabilities as well as advanced signal processing strategies. Multimodality in sensing as well as data processing is considered as an approach to strengthen the robustness of decision making for autonomous underwater robots. This chapter summarizes the current developments in sensing technology and opens new research questions with respect to sensing and signal processing using machine learning approaches.
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Kampmann, P., Bachmayer, R., Büscher, D., Burgard, W. (2020). Underwater Multi-modal Sensing for Environmental Mapping and Vehicle Navigation. In: Kirchner, F., Straube, S., Kühn, D., Hoyer, N. (eds) AI Technology for Underwater Robots. Intelligent Systems, Control and Automation: Science and Engineering, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-030-30683-0_12
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