A waypoint planning algorithm for an unmanned aerial vehicle (UAV) is presented that is teamed with an unmanned ground vehicle (UGV) for the task of search and rescue in a subterranean environment. The UAV and UGV are teamed such that the localization of the UAV is conducted on the UGV via the multisensor fusion of a fisheye camera, 3-D light detection and ranging, ranging radio, and a laser altimeter. Likewise, the trajectory planning of the UAV is conducted on the UGV, which is assumed to have a 3-D map of the environment (e.g., from simultaneous localization and mapping). The goal of the planning algorithm is to satisfy the mission's exploration criteria while reducing the localization error of the UAV by evaluating the belief space for potential exploration routes. The presented algorithm is evaluated in a relevant simulation environment where the planning algorithm is shown to be effective at reducing the localization errors of the UAV.

中文翻译：

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具有地下环境定位不确定性的 UAV/UGV 团队的搜索规划

提出了一种无人驾驶飞行器 (UAV) 的航路点规划算法，该算法与无人驾驶地面车辆 (UGV) 相结合，用于在地下环境中执行搜救任务。无人机和 UGV 组合在一起，通过鱼眼相机、3D 光检测和测距、测距无线电和激光高度计的多传感器融合，在 UGV 上进行无人机的定位。同样，UAV 的轨迹规划是在 UGV 上进行的，假设其具有环境的 3-D 地图（例如，来自同时的定位和映射）。规划算法的目标是通过评估潜在探索路线的置信空间来满足任务的探索标准，同时减少无人机的定位误差。