Abstract
In the last decade, with the wide application of UAVs in post-earthquake relief operations, the images and videos of affected areas obtained by UAVs immediately after a seismic event have become an important source of information for post-earthquake rapid assessment, which is crucial for initiating effective emergency response operations. In this study, we first consider the kinematic constraints of UAV and the Dubins curve is introduced to fit the shortest flyable path for each UAV that meets the maximum curvature constraint. Second, based on the actual requirements of post-earthquake rapid assessment, heterogeneous UAVs, multi-depot launching, and targets allowed access to multiple times, the paper proposes a multi-UAV rapid-assessment routing problem (MURARP). The MURARP is modeled as the multi-depot revisit-allowed Dubins TOP with variable profit (MD-RDTOP-VP) which is a variant of the team orienteering problem (TOP). Third, a hybrid genetic simulated annealing (HGSA) algorithm is developed to solve the problem. The result of numerical experiments shows that the HGSA algorithm can quickly plan flyable paths for heterogeneous UAVs to maximize the expected profit. Finally, a case study based on real data of the 2017 Jiuzhaigou earthquake in China shows how the method can be applied in a post-earthquake scenario.
Highlights
Rapid assessment after a catastrophic event, such as earthquake, is crucial to initiating effective emergency operations [1]
The results show that the hybrid genetic simulated annealing (HGSA) algorithm can obtain a high-quality feasible solution of the MD-RDTOP-VP model in a short time, which can meet the actual demand of quick path planning for each UAV in a post-earthquake scenario
Equation (6) is the objective function, corresponding to maximizing the expected profit of the multi-UAV post-earthquake rapid-assessment routing scheme, where wi is the weight of target i, pk is the error probability of the sensor carried by UAV k, yki is times that target i is visited by UAV k
Summary
Rapid assessment after a catastrophic event, such as earthquake, is crucial to initiating effective emergency operations [1]. The primary purpose of the multi-UAV rapid-assessment routing problem (MURARP) is to determine the extent of damage in the affected areas in different directions in the shortest possible time to carry out the rescue work in a targeted manner. The MURARP proposed in this paper can be regarded as a variant of the TOP in the real application of multi-UAV for post-earthquake rapid assessment task, in which UAVs equipped with sensors access a group of potential targets, such that the total expected profit can be maximized. The results show that the HGSA algorithm can obtain a high-quality feasible solution of the MD-RDTOP-VP model in a short time, which can meet the actual demand of quick path planning for each UAV in a post-earthquake scenario.
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