Micro aerial vehicles (MAVs) hold the potential for performing autonomous and contactless land surveys for the detection of landmines and explosive remnants of war (ERW). Metal detectors are the standard tool, but have to be operated close to and parallel to the terrain. As this requires advanced flight capabilities, they have not been successfully combined with MAVs before. To this end, we present a full system to autonomously survey challenging undulated terrain using a metal detector mounted on a 5 degrees of freedom (DOF) MAV. Based on an online estimate of the terrain, our receding-horizon planner efficiently covers the area, aligning the detector to the surface while considering the kinematic and visibility constraints of the platform. For resilient localization, we propose a factor-graph approach for online fusion of GNSS, IMU and LiDAR measurements. A simulated ablation study shows that the proposed planner reduces coverage duration and improves trajectory smoothness. Real-world flight experiments showcase autonomous mapping of buried metallic objects in undulated and obstructed terrain. The proposed localization approach is resilient to individual sensor degeneracy.
翻译:为探测地雷和战争遗留爆炸物,微型飞行器具有进行自主和无接触地面勘测的潜力。金属探测器是标准工具,但必须在接近地形和与地形平行运行。由于这需要先进的飞行能力,它们以前没有成功地与MAV相结合。为此目的,我们提出了一个完整的自动勘测系统,利用在自由5度上安装的金属探测器对无地地形进行不测勘测。根据对地形的在线估计,我们的后退对流平板仪有效地覆盖了该地区,将探测器与地面对齐,同时考虑到平台的动态和可见度限制。关于具有复原力的本地化,我们提出了全球导航卫星系统、IMU和LDAR测量的在线融合因子绘图方法。模拟的模拟实验室研究表明,拟议的规划仪缩短了覆盖时间,提高了轨迹的平滑性。现实世界飞行实验展示了在无隔热和阻断的地形对埋埋金属物体进行自动测绘的情况。拟议的地方化方法对单个传感器具有适应性。