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Two-Layer Path Planner for AUVs Based on the Improved AAF-RRT Algorithm

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Abstract

As autonomous underwater vehicles (AUVs) merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles, path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability. To overcome these problems, a specific two-player path planner based on an improved algorithm is designed. First, by combing the artificial attractive field (AAF) of artificial potential field (APF) approach with the random rapidly exploring tree (RRT) algorithm, an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed. Second, a two-layer path planner is designed with path smoothing, which combines global planning and local planning. Finally, as verified by the simulations, the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms, which are the basic RRT algorithm, the common AAF-RRT algorithm, and the improved AAF-RRT algorithm. Moreover, the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.

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Funding

Supported by Zhejiang Key R&D Program 558 No. 2021C03157, the “Construction of a Leading Innovation Team” project by the Hangzhou Munic-559 ipal government, the Startup funding of New-joined PI of Westlake University with Grant No. 560 (041030150118) and the funding support from the Westlake University and Bright Dream Joint In-561 stitute for Intelligent Robotics.

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Authors and Affiliations

  1. Zhejiang University-Westlake University Joint Training, Zhejiang University, Hangzhou, 310024, China

    Le Hong

  2. Key Laboratory of Coastal Environment and Resources of Zhejiang Province (KLaCER), School of Engineering, Westlake University, Hangzhou, 310024, China

    Le Hong, Changhui Song, Ping Yang & Weicheng Cui

  3. Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, 310024, China

    Le Hong, Changhui Song, Ping Yang & Weicheng Cui

Authors
  1. Le Hong
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  2. Changhui Song
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  3. Ping Yang
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  4. Weicheng Cui
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Corresponding author

Correspondence to Weicheng Cui.

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Article Highlights

• An improved AAF-RRT path planning algorithm for AUVs is proposed.

• The algorithm makes the attractive factor proportional to the distance between the point to be extended and the goal point.

• The algorithm is verified to have a better performance than the common AAF-RRT algorithm and basic RRT algorithm in terms of the search ability and ability to pass through narrow passages.

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Hong, L., Song, C., Yang, P. et al. Two-Layer Path Planner for AUVs Based on the Improved AAF-RRT Algorithm. J. Marine. Sci. Appl. 21, 102–115 (2022). https://doi.org/10.1007/s11804-022-00258-x

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  • DOI: https://doi.org/10.1007/s11804-022-00258-x

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