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High precision trajectory determination of an UAS by integrating camera and laser scanner data with generalised object models

通过将相机和激光扫描仪数据与广义物体模型相结合来确定无人机的高精度轨迹

基本信息

批准号：
315096149
负责人：
Professor Dr.-Ing. Christian Heipke
金额：
--
依托单位：
Geodätisches Institut
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/315096149?language=en
关键词：
precision trajectory determination UAS integrating

项目摘要

The aim of the submitted project is the integrated, cm-precise, reliable and high frequency determination of the trajectory of an unmanned aircraft system (UAS), equipped with different cameras and laser scanners. The focus is on methods showing real-time potential. Information from a building model according to level of detail 2 (LoD2) is integrated into the trajectory determination. In addition, it is supported by GNSS signals and IMU sensors. Availability of such a trajectory opens up a whole range of new possibilities in research, development and application. However, these will not be investigated in the current proposal.Trajectory determination is carried out in a sequential, robust parameter estimation as well as using a specific filter design, and extends the classical photogrammetric bundle adjustment for real-time use and the introduction of range information. The primary focus of the project is on the investigation of the added value in terms of accuracy and reliability brought about by the integration of cameras and laser scanners. The scientific novelty lies in the incorporation of generalised object space knowledge, combined with the simultaneous exploitation of observations for image coordinates and laser scanner measurements, for the high precision estimation of an UAS trajectory with real-time potential. Moreover, the approach can be transferred to any mobile mapping platform. For the first time, we match planes in 3D, generated from the sensor data, with those of the generalised building model on the one hand, and find correspondences between image and laser scanner data on the other hand. In this process, the object space information serves to stabilise the trajectory in the long term. This is particularly important in situations without GNSS reception. Additional corresponding planes, supporting the matching of image and laser scanner data, serve the short and medium term stabilisation of the trajectory. The results are validated based on simulations and experiments with real data involving independent reference information; the developed methods will be adapted and refined according to the results obtained. The scenario we have chosen for the project is the lower air space over urban terrain, which is known to have numerous GNSS signal outages, and for which a particularly precise trajectory is needed to prevent accidents such as a collision with obstacles.

提交的项目的目的是对配备不同相机和激光扫描仪的无人驾驶飞机系统（UAS）的轨迹进行集成，厘米精度，可靠和高频率的确定。重点是显示实时潜力的方法。根据细节等级2（LoD2）将来自建筑物模型的信息集成到轨迹确定中。此外，它还得到了GNSS信号和IMU传感器的支持。这种轨道的存在为研究、开发和应用开辟了一系列新的可能性。然而，这些将不会被调查在目前的proposal.Trajectory确定进行了一个连续的，强大的参数估计，以及使用一个特定的过滤器设计，并扩展了经典的摄影测量光束法平差的实时使用和范围信息的介绍。该项目的主要重点是调查相机和激光扫描仪集成带来的准确性和可靠性方面的附加值。科学上的新奇之处在于结合了一般的物体空间知识，并同时利用图像坐标和激光扫描仪测量的观测结果，以便对具有实时潜力的无人机系统轨迹进行高精度估计。此外，该方法可以被转移到任何移动的测绘平台。这是第一次，我们一方面将传感器数据生成的3D平面与广义建筑模型的平面相匹配，另一方面找到图像和激光扫描仪数据之间的对应关系。在这个过程中，物体空间信息用于长期稳定轨迹。这在没有GNSS接收的情况下尤其重要。额外的对应平面，支持图像和激光扫描仪数据的匹配，用于轨迹的短期和中期稳定。结果进行验证的基础上与真实的数据涉及独立的参考信息的模拟和实验，开发的方法将适应和完善，根据所获得的结果。我们为该项目选择的场景是城市地形上方的低空空间，已知该区域有许多GNSS信号中断，并且需要特别精确的轨迹来防止与障碍物碰撞等事故。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Assigning tie points to a generalised building model for UAS image orientation

将连接点分配给 UAS 图像定向的通用建筑模型

DOI：
10.5194/isprs-archives-xlii-2-w6-385-2017
发表时间：
2017
期刊：
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
影响因子：
0
作者：
Rottensteiner;Heipke
通讯作者：
Heipke

MOUNTING CALIBRATION OF A MULTI-VIEW CAMERA SYSTEM ON A UAV PLATFORM

DOI：
10.5194/isprs-annals-v-1-2021-97-2021
发表时间：
2021-06
期刊：
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
影响因子：
0
作者：
M. Mohammadi;A. Khami;F. Rottensteiner;I. Neumann;C. Heipke
通讯作者：
M. Mohammadi;A. Khami;F. Rottensteiner;I. Neumann;C. Heipke

Iterated Extended Kalman Filter with Implicit Measurement Equation and Nonlinear Constraints for Information-Based Georeferencing

具有隐式测量方程和非线性约束的迭代扩展卡尔曼滤波器用于基于信息的地理配准