A novel relative localization approach for cooperative guidance of a micro-scale Unmanned Aerial Vehicle (UAV) fusing Visual-Inertial Odometry (VIO) with Light Detection and Ranging (LiDAR) is proposed in this paper. LiDAR-based localization is accurate and robust to challenging environmental conditions, but 3D LiDARs are relatively heavy and require large UAV platforms. Visual cameras are cheap and lightweight. However, visual-based self-localization methods exhibit lower accuracy and can suffer from significant drift with respect to the global reference frame. We focus on cooperative navigation in a heterogeneous team of a primary LiDAR-equipped UAV and secondary camera-equipped UAV. We propose a novel cooperative approach combining LiDAR relative localization data with VIO output on board the primary UAV to obtain an accurate pose of the secondary UAV. The pose estimate is used to guide the secondary UAV along trajectories defined in the primary UAV reference frame. The experimental evaluation has shown the superior accuracy of our method to the raw VIO output and demonstrated its capability to guide the secondary UAV along desired trajectories while mitigating VIO drift.

翻译：本文提出了一种面向微型无人机协同制导的新型相对定位方法，该方法融合了视觉-惯性里程计与激光雷达技术。基于激光雷达的定位在复杂环境条件下具有高精度和鲁棒性，但三维激光雷达重量较大，需要搭载于大型无人机平台。视觉相机成本低廉且重量轻便，然而基于视觉的自定位方法精度较低，且易出现相对于全局参考系的显著漂移。本研究聚焦于异构无人机团队（搭载激光雷达的主无人机与搭载视觉相机的从无人机）的协同导航，提出了一种创新性协同方法：在主无人机端将激光雷达相对定位数据与视觉-惯性里程计输出进行融合，从而获得从无人机的精确位姿估计。该位姿估计值用于引导从无人机沿主无人机参考系中定义的轨迹运动。实验评估表明，本方法在精度上显著优于原始视觉-惯性里程计输出，并验证了其在抑制视觉-惯性里程计漂移的同时，引导从无人机沿期望轨迹飞行的能力。