UAV-UGV Cooperative Trajectory Optimization and Task Allocation for Medical Rescue Tasks in Post-Disaster Environments

TL;DR

This paper presents a novel cooperative framework using UAVs and UGVs for optimized medical rescue in post-disaster scenarios, integrating advanced algorithms for task allocation and trajectory planning to significantly improve efficiency.

Contribution

It introduces a combined genetic algorithm, informed-RRT*, and CMA-ES approach for task allocation and trajectory optimization in UAV-UGV rescue missions, enhancing efficiency and scalability.

Findings

Reduces mission completion time by over 73% compared to traditional methods.

Achieves a 15.1% reduction in total traveled distance after optimization.

Demonstrates effectiveness in realistic post-disaster simulation environments.

Abstract

In post-disaster scenarios, rapid and efficient delivery of medical resources is critical and challenging due to severe damage to infrastructure. To provide an optimized solution, we propose a cooperative trajectory optimization and task allocation framework leveraging unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). This study integrates a Genetic Algorithm (GA) for efficient task allocation among multiple UAVs and UGVs, and employs an informed-RRT* (Rapidly-exploring Random Tree Star) algorithm for collision-free trajectory generation. Further optimization of task sequencing and path efficiency is conducted using Covariance Matrix Adaptation Evolution Strategy (CMA-ES). Simulation experiments conducted in a realistic post-disaster environment demonstrate that our proposed approach significantly improves the overall efficiency of medical rescue operations compared to traditional strategies. Specifically, our method reduces the total mission completion time to 26.7 minutes for a 15-task scenario, outperforming K-Means clustering and random allocation by over 73%. Furthermore, the framework achieves a substantial 15.1% reduction in total traveled distance after CMA-ES optimization. The cooperative utilization of UAVs and UGVs effectively balances their complementary advantages, highlighting the system's scalability and practicality for real-world deployment.