Citation: Zhang, H.; Huang, Y.; Qin,
H.; Geng, Z. USV Search Mission
Planning Methodology for Lost
Target Rescue on Sea. Electronics 2023,
12, 4584. https://doi.org/10.3390/
electronics12224584
Academic Editor: Felipe Jiménez
Received: 18 September 2023
Revised: 1 November 2023
Accepted: 7 November 2023
Published: 9 November 2023
Copyright: © 2023 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/).
Article
USV Search Mission Planning Methodology for Lost Target
Rescue on Sea
Han Zhang, Yanyan Huang *, Hucheng Qin and Ze Geng
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;
zhanghan@njust.edu.cn (H.Z.); qhc1502@njust.edu.cn (H.Q.); gz65535@njust.edu.cn (Z.G.)
* Correspondence: huangyy@njust.edu.cn
Abstract:
Quick and efficient mission planning is essential in maritime search and rescue (SAR).
This includes defining the search area and developing an effective strategy. The task is fraught
with challenges due to the difficulty of determining location information and the impact of complex
meteorological environments. The primary objective of SAR mission planning is the rapid deployment
of unmanned surface vehicles (USVs) to the incident area. While many planning algorithms prioritize
the shortest route, there’s a lack of mission planning measures that maximize SAR effectiveness. In
addition, the joint deployment of USVs increases the success rate compared to individual operations.
Therefore, this paper presents a task assignment framework for USVs in SAR missions that considers
the probability of success and time constraints. USVs are used to search for lost targets, and the
framework consists of the following three modules: (1) a module for predicting the location of the
overboard target to be rescued; (2) a module for modeling the probability of mission success; (3) a
module for assigning search tasks to USVs. The framework first analyzes the search area. Then, it
predicts the target location with a stochastic particle method, which incorporates marine environment
forecast data to update the mission target location. To improve the scientific nature of USV search
and rescue mission plans, an evaluation model is developed to assess mission capability. Simulation
experiments and task scheme analysis validate its effectiveness.
Keywords: cooperative path planning; missing target; mission efficiency; search and rescue
1. Introduction
As the primary mode of international freight transportation, more than 90 percent of
the world’s trade is carried by sea each year. However, maritime transportation is prone
to frequent accidents due to the complex and dynamic marine environment influenced
by both natural and human factors. According to data released by the China Maritime
Search and Rescue Center (CMSARC) for the period from February to June 2023, a total
of 546 SAR operations were conducted. During these operations, a total of 2847 search
and rescue vessels and 66 search and rescue aircraft were deployed and 363 vessels in
distress and 3481 people were successfully rescued. Remarkably, these efforts saved the
lives of 3392 people. These statistics underscore the increasing frequency of maritime
accidents, driven by the rapid expansion of the shipping industry. Therefore, improving
China’s maritime search and rescue capabilities has become a matter of paramount research
importance.
At present, emergency search and rescue at sea relies mainly on manually operated
search vessels. This method is limited by the ability of search equipment and humans to
coordinate, resulting in longer search times, lower efficiency, and an increased chance of
missing search and rescue targets. However, the USV offers a promising solution. It has
autonomous navigation, control, and communication capabilities. They possess character-
istics such as high mobility, cost-effectiveness, and large search radius [
1
], and represent
a novel technological approach to address the weaknesses in coordinated maritime SAR
Electronics 2023, 12, 4584. https://doi.org/10.3390/electronics12224584 https://www.mdpi.com/journal/electronics
