Recovery Path Planning for Autonomous Underwater Vehicles Using Constrained Bi-RRT*-Smart Algorithms

Zhenchi Zhang, Haibo Wu, Heng Zhou, Yunxuan Song, Yimin Chen, Ke He, Jian Gao

202310 citationsDOI

Abstract

In this paper, a constrained bi-RRT*-smart algorithm is proposed to solve the recovery path planning problem of an Autonomous Underwater Vehicle (AUV). The RRT*-smart algorithm is taken as a basic strategy for the predefined path-planning problem to generate an optimal path which has the smallest distance and no collisions with the islands. On this basis, a bi-direction technique is fusion with the RRT*-smart algorithm to get a bi- RRT*-smart algorithm. Additionally, two practical constraints are considered to facilitate the feasibility of the proposed method in real applications. For one thing, considering the limited turning ability of the AUV. For another, a local direction constraint is set near the ending point to ensure that the AUV enters the docking station along a reasonable direction. Compared with the previous algorithms, it not only reduces the path cost, but also greatly improves the convergence rate. Simulation results confirm the efficiency of the proposed bi-RRT*- smart algorithm.

Topics & Concepts

Motion planningPath (computing)AlgorithmConvergence (economics)Computer scienceUnderwaterMathematical optimizationConstraint (computer-aided design)Set (abstract data type)Real-time computingEngineeringRobotArtificial intelligenceMathematicsComputer networkOceanographyEconomicsMechanical engineeringProgramming languageEconomic growthGeologyRobotic Path Planning AlgorithmsUnderwater Vehicles and Communication SystemsOptimization and Search Problems