lidar | 易学教程

Real time point cloud processing and latency

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问题 Our project is to integrate Lidar system into virtual reality (unity). I could achieve that integration with ROS-bridge. Next step is to process the point cloud data before we send it to unity system. Lidar sensor velodyne VLP-16 Ubuntu 18.4 IDE: Pycharm (python) Point cloud processing: python point cloud library with ROS ros-bridge with unity system Problem Without processing, there is only 1 second latency from sensor to unity visualization. But processing point-cloud data in ROS(pycharm)

Convert XYZ point cloud to grayscale image

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问题 Everyone I'm trying to convert point cloud (X, Y, Z) to the grayscale image using python. I learned that the grayscale image could be generated by a Numpy array. But what I have now is a set of points which contains X, Y and height. I wanna generate a grayscale image based on X, Y and grayscale value which is Height. Can someone give me an idea about this? Thanks beforehand. Rowen 回答1: let's assume that the X,Y are arranged so they will form a grid (which is mandatory in order to build a

Unable to initialize point cloud - ORA-13249: Error creating dml trigger

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问题 I'm unable to initialize point cloud in Oracle Database 12c. Trying to execute following commands: CREATE TABLE point_clouds( id NUMBER, capture_ts TIMESTAMP, point_cloud SDO_PC ); CREATE TABLE pc_blocks AS select * from mdsys.sdo_pc_blk_table; INSERT INTO point_clouds (id, point_cloud) VALUES ( 1001, sdo_pc_pkg.init( basetable => 'point_clouds', basecol => 'point_cloud', blktable => 'pc_blocks', ptn_params => 'blk_capacity=10000', pc_extent => mdsys.sdo_geometry( 2003, 8307, null, mdsys.sdo

how to re-render the scanned mesh content with realityKit's ARView?

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问题 I can modify the line color of the mesh using the following code. extension ARMeshClassification { var description: String { switch self { case .ceiling: return "Ceiling" case .door: return "Door" case .floor: return "Floor" case .seat: return "Seat" case .table: return "Table" case .wall: return "Wall" case .window: return "Window" case .none: return "None" @unknown default: return "Unknown" } } var color: UIColor { switch self { case .ceiling: return .red case .door: return .green case

LiDAR and RealityKit – Capture a Real World Texture for a Scanned Model

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来源： https://stackoverflow.com/questions/63793918/lidar-and-realitykit-capture-a-real-world-texture-for-a-scanned-model

LiDAR and RealityKit – Capture a Real World Texture for a Scanned Model

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来源： https://stackoverflow.com/questions/63793918/lidar-and-realitykit-capture-a-real-world-texture-for-a-scanned-model

LiDAR and RealityKit – Capture a Real World Texture for a Scanned Model

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来源： https://stackoverflow.com/questions/63793918/lidar-and-realitykit-capture-a-real-world-texture-for-a-scanned-model

iPad Pro Lidar - Export Geometry & Texture

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问题 I would like to be able to export a mesh and texture from the iPad Pro Lidar. There's examples here of how to export a mesh, but Id like to be able to export the environment texture too ARKit 3.5 – How to export OBJ from new iPad Pro with LiDAR? ARMeshGeometry stores the vertices for the mesh, would it be the case that one would have to 'record' the textures as one scans the environment, and manually apply them? This post seems to show a way to get texture co-ordinates, but I can't see a way

ARKit 3.5 – How to export OBJ from new iPad Pro with LiDAR?

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问题 How can I export the ARMeshGeometry generated by the new SceneReconstruction API on the latest iPad Pro to an .obj file? Here's SceneReconstruction documentation. 回答1: Starting with Apple's Visualising Scene Scemantics sample app, you can retrieve the ARMeshGeometry object from the first anchor in the frame. The easiest approach to exporting the data is to first convert it to an MDLMesh: extension ARMeshGeometry { func toMDLMesh(device: MTLDevice) -> MDLMesh { let allocator =

激光雷达（LIDAR） vs. 雷达（RADAR）

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激光雷达（LIDAR） vs. 雷达（RADAR） 1、定义 LIDAR---------Light Detection And Ranging 即激光探测与测距 RADAR-------radio detection and ranging 即无线电探测与测距 2、波的区别 Rada采用无线电波，使用的波长是4-12mm; LIDAR使用的激光波长通常在900-1500nm之间。 3、工作原理 lidar传感器主要分为两种，一种是基于三角测距的；另一种是基于飞行时间（TOF）的； LiDAR传感器快速发射激光脉冲（通常最高可达每秒150000次脉冲），激光信号到达障碍物后反射回LiDAR传感器。传感器通过测量激光信号从发射到返回的时间，精确计算确定传感器到障碍物之间的距离，它还能探测目标物体的准确尺寸。LiDAR通常用于高分辨率地图的绘制。 RADAR系统的工作原理跟LiDAR很相似，唯一的区别在于RADAR采用的是无线电波而非激光。在RADAR系统中，其天线既可以作为雷达接收器也可以作为发射器。不过，和光波相比，在与被测物体接触时，无线电波的吸收较少，因此，RADAR的有效工作距离相对更远。RADAR技术最广为人知的应用，应该是军事用途了。飞机和战舰都会装备RADAR来测量高度，或探测附近其它的运输设备和物体。 4、用途 LiDAR传感器常用于周围环境的实时3D地图创建