USV Search Mission Planning Methodology for Lost Target Rescue on Sea

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.