Recent Advances in AI for Navigation and Control of Underwater Robots
Leif Christensen, José de Gea Fernández, Marc Hildebrandt, Christian Ernst Siegfried Koch, Bilal Wehbe
Editors: Springer
In Current Robotics Reports, Springer, volume n.n., pages n.n.-n.n., Jul/2022.
Abstract
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Purpose of review: The goal of this paper is to review current developments in the area of underwater robotics regarding the use of AI, especially in model learning, robot control, perception and navigation as well as manipulation.
Recent findings: AI technologies and advanced control techniques are finding their way into robotics systems to deal with complex and challenging conditions and to equip them with higher levels of autonomy.
Summary: Although AI techniques and concepts are already a focus area in research on autonomous underwater systems, broad adoption to commercial systems is still in its infancy. Nonetheless, major advances have been done in recent years, especially on integrating different capabilities (perception, navigation, advanced control) in a single system and with first approaches on interaction and autonomous manipulation.
Keywords
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AI, underwater robotics, AUV, machine learning, model learning, control
Links:
https://link.springer.com/article/10.1007/s43154-022-00088-3
