Cyl-IRRT: Homotopy Optimal 3D Path Planning for AUVs by Biasing the Sampling Into a Cylindrical Informed Subset

In a complex 3-D environment, efficiently and safely reaching the target position is of great significance for autonomous underwater vehicles. This article proposes a cylinder-based informed rapid exploration random tree (Cyl-iRRT*) algorithm, which seeks to find the homotopy optimal path by focusin...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) Vol. 70; no. 4; pp. 3985 - 3994
Main Authors: Yu, Fujie, Chen, Yuan
Format: Journal Article
Language:English
Published: New York IEEE 01.04.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Autonomous underwater vehicle (AUV)
Autonomous underwater vehicles
Cylinders
optimal path planning
Optimization
Path planning
Planning
Probabilistic logic
rapidly exploring random tree (RRT)
Sampling
sampling-based algorithms
Search problems
Task analysis
Three-dimensional displays
Trajectory
ISSN:0278-0046, 1557-9948
Online Access:Get full text
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Summary:In a complex 3-D environment, efficiently and safely reaching the target position is of great significance for autonomous underwater vehicles. This article proposes a cylinder-based informed rapid exploration random tree (Cyl-iRRT*) algorithm, which seeks to find the homotopy optimal path by focusing the search space on the designed gradually shrinking cylinder. The proportional shrinkage method and obstacle-based sampling strategy are presented to yield a fast convergence response and robust stability. Furthermore, the probabilistic completeness and homotopic optimality of Cyl-iRRT* are proven to be effective. Finally, both simulation and real-world experimental results reveal the superiorities of the Cyl-iRRT* algorithm.
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ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2022.3177801