Visual Inertial System (VIS) Technology

Some years ago, during our technology screening process at the Hexagon Technology Centre, we identified the development need for Visual Simultaneous Localization and Mapping (SLAM) technology for the Hexagon group. It was clear from the beginning that this technology could be applied to determine the position of devices in 3D-space and would be highly beneficial for future innovations. We started with the first implementation of a generic Visual SLAM algorithm and investigated the potential of this technology for various applications relevant to our business areas.

What is Visual SLAM?

In principle, Visual SLAM is nothing more than a repetitive application of resection and forward-intersection with an optional bundle-adjustment at the very end. These basic algorithms are well known from photogrammetry for more than a century. However, the developments in feature tracking and feature matching triggered by computer vision and robotics – that made the manual selection of tie points obsolete – enabled the implementation of an automated workflow.

基于视觉量的3D空间导航非常直观。它的工作原理与我们人类在世界上的导航方式非常相似。当我们走向一个物体时，例如建筑物，对象在我们的视野中变得更大。当我们向后走时，它会变小。

In Visual SLAM the feature tracking is detecting point features – or so-called landmarks – in the image stream and tracks their position from one image frame to the next. Now, when the camera moves towards a building, the detected features, e.g. the corners of the building, or the door or the windows, will then move from the image centre outwards since the building is getting larger in the field of view. When the camera is rotating from left to right the features on the image would then move to the right and to the left. Hence, from the movement of the feature points between the frames of the image stream, Visual SLAM can deduce the direction of motion of the camera in 3D-space.

In a continuous process, the SLAM algorithm computes the 3D-coordinates (mapping) of the tracked features from two or more positions and uses these coordinates for the determination of the following position (localisation). The generated map of landmarks is evolving as the operator moves along this track to the next scanner setup and acts as a reference for the whole positioning algorithm. Consequently, this map that is built up and maintained during the process is essential to keep the drift error small.

There are alternative approaches based on inertial measurements only. An Inertial Measurement Unit (IMU) provides measurements for accelerations and angular rates that are integrated to derive velocity in a first step and finally position and orientation of the device. Since these measurements are affected by measurement errors, the integration leads to a significant drift of the derived quantities. Since in this approach a map as an overall reference is missing, the resulting drift is significantly higher than in Visual SLAM. Although, an optimal result cannot be achieved based on inertial measurements only, the data from the IMU can be fused with the image measurements and support Visual SLAM.

How does Visual SLAM redefine the registration process?

激光扫描的典型注册，即单个扫描与一个组合点云的组合，是在使用后处理软件在办公室进行完整的数据后执行的。在办公室时，通常是操作员第一次能够调查扫描项目的结果并检查数据采集的完整性。操作员可能会识别一些缺失的区域，他们可能必须返回站点并进行其他扫描。有时，如果项目位置远离办公室的情况，则可以与一段时间的开车相关联，因此，客户希望不惜一切代价避免使用。

几次激光扫描的现场预注册是当时陆地激光扫描商业总监Juergen Mayer的新功能，这将完全解决昂贵的返工。每次扫描后，目的是在现场中获得的数据，将自动注册，并在先前的扫描数据中自动注册。然后，应在移动平板电脑上可视化所得的组合云。这将使客户能够立即研究捕获的数据以及可能缺少哪些数据，以最佳计划下一个扫描仪设置，最重要的是，在仍在现场时执行完整性检查。

This was discovered during our feasibility study and finally we could show that the concept would work in practice as well. Based on these findings, together with our colleagues from the business unit, the development of the product started and ended with the announcement of theLeica RTC360在HXGN Live 2018。

Could Visual SLAM be the basis for this new field registration feature?

Theoretically it was obvious that based on Visual SLAM, the motion between two scanning setups should be determined. Knowing the translation and rotation, the point cloud resulting from the current scan can automatically be aligned with the point cloud from the previous scan. The goal was to then prove that the concept would work in practice.

视觉惯性系统（VIS）技术不应在当时进行的激光扫描工作流程上添加任何约束。这意味着操作员不应受到一些其他规则的影响，例如以特定方式携带激光扫描仪。这是可行性研究开始的主要要求之一。即使RTC360的一侧被阻塞，例如在操作员的主体上，VIS技术仍应起作用。从根本上讲，这是RTC360中内置五个VIS相机的主要原因。此外，应实时进行自动预注册的处理，以使操作员在执行下一次扫描后立即获得结果。鉴于此，我们的视觉大满贯算法必须证明它可以很好地整合到陆地激光扫描的工作流程中。

What’s next?

In the meantime at the Hexagon Technology Centre, quite some other applications for Visual SLAM have been investigated. Although the basic principle is the same it always needs some fine tuning and adaptations to a specific setting and workflow in order to achieve the best results. A highlight in this context is the development of the LeicaBLK2GO手持式成像激光扫描仪，其中视觉猛击与LiDAR SLAM结合使用，将算法提升到一个新的水平。这只是该技术证明其适用于定位工作流程的许多例子。其中一些已经作为产品发布了，将来可以预期更多的产品，从而丰富整个Hexagon GeoSystems的产品组合。bob体育报道