3D Occupancy Grid for AGV-UAV Coordination

该数据集是一个从Gazebo环境中生成的3D占用网格，旨在为自动导引车（AGV）和无人机（UAV）的路径查找任务提供便利。该网格用于对包括3D-A*、3D-CBS以及基于学习的方法（DCC）在内的多种算法进行基准测试，同时支持抽象位置更新和低级别运动控制。该数据集涵盖了6架无人机和16辆自动导引车，它们在具有独特起点和终点位置的不同环境中进行任务。具体任务是为自动导引车和无人机在不同环境下的多代理路径查找（MAPF）问题提供解决方案。

This dataset is a 3D occupancy grid generated from the Gazebo environment, designed to facilitate path finding tasks for Automated Guided Vehicles (AGVs) and Unmanned Aerial Vehicles (UAVs). It is used to benchmark multiple algorithms including 3D-A*, 3D-CBS, and the learning-based method DCC, while supporting abstract position updates and low-level motion control. The dataset covers 6 UAVs and 16 AGVs performing tasks in distinct environments with unique start and goal positions. Its core purpose is to provide solutions for multi-agent path finding (MAPF) problems of AGVs and UAVs across different environments.