Hui Yu, Anwen Shen, and Yansen Su
Hybrid search algorithms, path planning, Fast Marching (FM),autonomous underwater vehicles (AUVs)
In this paper, we present a new continuous smooth motion planning algorithm for autonomous underwater vehicles (AUVs) used in complex and dynamic underwater environments. Existing motion planning algorithms in artificial intelligence are not designed to deal with complex and dynamic continuous underwater environments prone to currents. We present a novel Fast Marching (FM) method to address the following issues. First, we develop an algorithm called Hybrid Search Fast Marching (HSFM) method, which gives consideration to both total path cost and computational time, to efficiently generate a 3D continuous smooth path from a discrete representation of underwater environments. Second, we develop a novel anisotropic FM algorithm to deal with underwater currents based on the geometric relationships between characteristic lines and gradient lines in speed profiles. Third, we introduce multiple decision criteria and constraints in complex and dynamic underwater environments such as currents, dynamic obstacles, reefs, shoals and navigation rules in motion planning process. Extensive random simulations for an AUV sail planning task show that the HSFM algorithm meets the time constraints of online replanning and finds continuous smooth paths of better cost in shorter time compared to the MSA and A algorithms.
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