论文标题
室内环境中的基于无人机的体积估计
Drone-based Volume Estimation in Indoor Environments
论文作者
论文摘要
在机器人检查工业仓库中，大型室内空间中的体积估计是一个重要的挑战。我们提出了一种使用视觉特征进行室内定位和2D-LIDAR测量的表面重建的视觉特征来对自主系统进行体积估算的方法。一个基于高斯的过程模型结合了从测量结果中收集的有关地形的统计先验信息，从中计算了体积估算。我们的算法找到可行的轨迹，可最大程度地减少体积估计值的不确定性。我们显示了对地形数据的表面重建和体积估计的模拟结果。
Volume estimation in large indoor spaces is an important challenge in robotic inspection of industrial warehouses. We propose an approach for volume estimation for autonomous systems using visual features for indoor localization and surface reconstruction from 2D-LiDAR measurements. A Gaussian Process-based model incorporates information collected from measurements given statistical prior information about the terrain, from which the volume estimate is computed. Our algorithm finds feasible trajectories which minimize the uncertainty of the volume estimate. We show results in simulation for the surface reconstruction and volume estimate of topographic data.
