Citation: Li, J.; Li, C.; Chen, T.;
Zhang, Y. Improved RRT Algorithm
for AUV Target Search in Unknown
3D Environment. J. Mar. Sci. Eng.
2022, 10, 826. https://doi.org/
10.3390/jmse10060826
Academic Editor: Jacopo Aguzzi
Received: 21 April 2022
Accepted: 14 June 2022
Published: 17 June 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Journal of
Marine Science
and Engineering
Article
Improved RRT Algorithm for AUV Target Search in Unknown
3D Environment
Juan Li , Chengyue Li, Tao Chen * and Yun Zhang
Institute of Ocean Installations and Control Technology, College of Intelligent Systems Science and Engineering,
Harbin Engineering University, Harbin 150001, China; lijuan041@hrbeu.edu.cn (J.L.);
lichengyue@hrbeu.edu.cn (C.L.); 18341315841@163.com (Y.Z.)
* Correspondence: chentao409@hrbeu.edu.cn
Abstract:
Due to the complexity of the marine environment, underwater target search and intercep-
tion is one of the biggest problems faced by an autonomous underwater vehicle (AUV). At present,
there is quite a lot of research in terms of the two-dimensional environment. This paper proposes an
improved rapidly exploring random trees (RRT) algorithm to solve the problem of target search and
interception in an unknown three-dimensional (3D) environment. The RRT algorithm is combined
with rolling planning and node screening to realize path planning in an unknown environment,
and then the improved RRT algorithm is applied to the search and interception process in a 3D
environment. Combined with the search decision function and the three-point numerical differential
prediction method, the RRT algorithm can search for and effectively intercept the target. Numerical
simulations in various situations show the superior performance, in terms of time and accuracy, of
the proposed approach.
Keywords: target search; AUV; path planning; RRT; interception
1. Introduction
An autonomous underwater vehicle (AUV) is a powerful tool for exploring the un-
known marine environment. With the development of science and society, artificial intel-
ligence, electronic computers, and other high-tech performance technologies have made
continuous progress. In most countries, AUVs have become the focus of marine technology
research [1,2].
With the wide application range of AUVs, there are increasing restrictions and limi-
tations regarding research using AUVs. Underwater unmanned technology is only a few
decades old. The existence of fish and glaciers in the marine environment make it difficult
for AUVs to carry out underwater unmanned operation, while an AUV’s own energy
consumption and communication restriction also limit the efficiency of underwater mis-
sions. Research on how to realize the target search and complete the corresponding tasks
scientifically and efficiently in the complex 3D environment has been gaining popularity
among scholars [3–5].
Juan [
6
] proposed a multi-AUV target search method based on dynamic prediction
from two aspects, (i) improving underwater target search efficiency and (ii) positioning
accuracy, and formulated three search strategies according to the existence of targets in the
environment. However, the algorithm is simulated only in the two-dimensional environ-
ment and should be extended to the 3D environment before it is applied in practice, so as
to meet the practical application scenarios. Jianjun [
7
] proposed a search algorithm based
on improved DSA for AUV collaborative target search in a 3D environment. The algorithm
improves the detection ability of the DSA algorithm by synthesizing the Levyflight algo-
rithm based on fuzzy rules and is verified and compared with the general DSA algorithm
and the PSO algorithm in the simulation. Although a search method for a 3D environment
is proposed, the search time exceeds expectations. Ishida [
8
] proposed the moving tart
J. Mar. Sci. Eng. 2022, 10, 826. https://doi.org/10.3390/jmse10060826 https://www.mdpi.com/journal/jmse
