{"id":11803,"date":"2026-05-19T14:30:19","date_gmt":"2026-05-19T14:30:19","guid":{"rendered":"https:\/\/www.oxts.com\/?p=11803"},"modified":"2026-05-19T14:30:40","modified_gmt":"2026-05-19T14:30:40","slug":"what-is-a-point-cloud-2026","status":"publish","type":"post","link":"https:\/\/www.oxts.com\/zh\/what-is-a-point-cloud-2026\/","title":{"rendered":"\u4ec0\u4e48\u662f\u70b9\u4e91\uff1f\u00a0"},"content":{"rendered":"\n
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What is a point cloud? <\/h3>\n\n \n\n\n \n\n\n\n
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Point clouds are data files created by LiDAR scanners. They are made up of millions, or even billions, of \u201cpoints\u201d which are\u00a0essentially reflections\u00a0off a surface picked up by the scanner.<\/span>\u00a0<\/span><\/p>\n

A\u00a0LiDAR scanner works\u00a0by\u00a0firing\u00a0pulses of light (LiDAR stands for Light Detection and Ranging), and\u00a0measuring\u00a0how long those pulses take to bounce back after hitting an object. Using the speed of light and that time measurement, the LiDAR works out how far away from the scanner each point is.<\/span>\u00a0<\/span><\/p>\n

By sending out millions of pulses, a LiDAR scanner quickly builds up a detailed picture of the environment around it. Some LiDAR scanners only provide 2D scans, which look more like floor plans. Others produce a 3D point cloud. Additionally, some scanners are static \u2013 they only fire pulses in front of them \u2013 while others spin, sending pulses all around the scanner to build a\u00a0360\u00b0 point\u00a0cloud.<\/span>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

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What are point clouds used for?<\/h5>\n\n\n
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There are three things you can do with a point cloud:<\/span>\u00a0<\/span><\/p>\n

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  1. You can use it to measure distances between various points and your scanner (and therefore whatever it is mounted to).<\/span>\u00a0<\/span><\/li>\n
  2. You can use it\u00a0to measure distances between two points within the cloud.<\/span>\u00a0<\/span><\/li>\n
  3. You can use it to create a model of the environment around you.<\/span>\u00a0<\/span><\/li>\n<\/ol>\n

    Because of the volume of pulses sent out by a LiDAR scanner, the measurements you can take from a point cloud are\u00a0generally very\u00a0precise and\u00a0very\u00a0reliable.\u00a0From those core uses for point\u00a0clouds,\u00a0you can do\u00a0a number of\u00a0things with the data.<\/span>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

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    Using point clouds in surveying and mapping<\/h5>\n\n\n
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    By\u00a0<\/span>mounting a LiDAR on a rover or an aerial vehicle<\/span><\/a>, you can\u00a0survey large areas of land quickly and in\u00a0great detail.\u00a0Surveyors can then use that data to take\u00a0accurate\u00a0measurements for a range of uses. A popular use of LiDAR, for instance, is to survey\u00a0a space\u00a0that an autonomous mobile robot will\u00a0operate\u00a0in. The point cloud can then be transformed into a map that can be fed into the AMR\u2019s control stack,\u00a0so it can plan a route through a space and navigate there without crashing.<\/span>\u00a0<\/span><\/p>\n

    To use point clouds for surveying\u00a0and mapping,\u00a0it\u2019s\u00a0vital that the point clouds are georeferenced \u2013\u00a0we\u2019ll\u00a0come on to that later.<\/span>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

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    Using point clouds in surveying and mapping<\/h5>\n\n\n
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    By\u00a0<\/span>mounting a LiDAR on a rover or an aerial vehicle<\/span><\/a>, you can\u00a0survey large areas of land quickly and in\u00a0great detail.\u00a0Surveyors can then use that data to take\u00a0accurate\u00a0measurements for a range of uses. A popular use of LiDAR, for instance, is to survey\u00a0a space\u00a0that an autonomous mobile robot will\u00a0operate\u00a0in. The point cloud can then be transformed into a map that can be fed into the AMR\u2019s control stack,\u00a0so it can plan a route through a space and navigate there without crashing.<\/span>\u00a0<\/span><\/p>\n

    To use point clouds for surveying\u00a0and mapping,\u00a0it\u2019s\u00a0vital that the point clouds are georeferenced \u2013\u00a0we\u2019ll\u00a0come on to that later.<\/span>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

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    The importance of georeferencing point clouds<\/h5>\n\n\n
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    As\u00a0we\u2019ve\u00a0said, surveying and mapping applications need a georeferenced point cloud to work. That means that each point\u00a0must\u00a0have a defined position, either in relation to the earth (in a global frame) or in relation to a known fixed point (a local frame).\u00a0This allows users to put the point cloud data in context, so it can be used.<\/span>\u00a0<\/span><\/p>\n

    To\u00a0georeference\u00a0point cloud data, you need a device attached to the payload or platform the LiDAR is mounted on that provides position data.\u00a0That\u2019s\u00a0where hardware like our GNSS\/INS comes in.<\/span>\u00a0<\/span><\/p>\n

    A GNSS\/INS\u00a0is a device that\u00a0combines\u00a0data from GNSS satellites\u00a0and\u00a0an\u00a0inertial measurement unit\u00a0to provide an\u00a0estimate of the GNSS\/INS\u2019\u00a0position\u00a0(and\u00a0the position of\u00a0whatever it is attached to) on the earth.\u00a0A GNSS\/INS is designed to give you\u00a0accurate\u00a0and robust position data \u2013 which you can combine with your LiDAR data to\u00a0georeference\u00a0your point cloud.<\/span>\u00a0<\/span><\/p>\n

    OXTS has a range of different GNSS\/INS devices\u00a0that you can use for georeferencing point cloud data. Some are designed for aerial\u00a0mapping activities, such as our\u00a0<\/span>xNAV650<\/span><\/a>, while others are designed\u00a0for pinpoint accuracy including\u00a0our\u00a0<\/span>RT3000 v4<\/span><\/a>.\u00a0<\/span>\u00a0<\/span><\/p>\n

    See our\u00a0full range of GNSS\/INS devices<\/span><\/b><\/a>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

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    OXTS georeferencing and point cloud tools<\/h5>\n\n\n
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    At O<\/span>X<\/span>TS\u00a0<\/span>we\u2019ve<\/span>\u00a0<\/span>developed tools that help make it easier to\u00a0<\/span>georeference<\/span>\u00a0point clouds, as well as some advanced tools that let you get even more value from point cloud data.<\/span><\/span>\u00a0<\/span><\/p>\n

    OXTS Georeferencer<\/strong><\/h6>\n

    O<\/span>X<\/span>TS\u00a0<\/span>Georeference<\/span>r<\/span>\u00a0is built specifically to\u00a0<\/span>combine location data from your GNSS\/INS with raw LiDAR data, to produce a georeferenced point cloud.\u00a0<\/span>You load up your LiDAR data and your\u00a0<\/span>GNSS\/<\/span>INS data, press go, and\u00a0<\/span>the system takes care of the rest<\/span>.<\/span>\u00a0<\/span>The\u00a0<\/span>final point<\/span>\u00a0cloud output can then be used in\u00a0<\/span>a range of mapping software and tools.<\/span><\/span>\u00a0<\/span><\/p>\n

    Boresight Calibration Tool<\/strong><\/h6>\n

    One of the biggest challenges when georefer<\/span>encing point cloud data is\u00a0<\/span>eliminating<\/span>\u00a0blurriness and \u201cdouble vision\u201d from the point cloud (objects appearing twice). These issues are caused by slight misalignments between the LiDAR and the\u00a0<\/span>GNSS\/<\/span>INS, and the O<\/span>X<\/span>TS Boresight Calibration Tool fixes them. It requires around two minutes of\u00a0extra driving at the start of a survey \u2013 but it dramatically improves the quality of your\u00a0final point\u00a0cloud.<\/span><\/span><\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n \n

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    LiDAR Boost<\/h5>\n\n\n
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    LiDAR Boost is a technology designed to improve accuracy in GNSS-denied spaces. It works by\u00a0analysing individual snapshots from an automotive LiDAR,\u00a0identifying\u00a0planes that\u00a0indicate\u00a0things like walls and corners, and comparing how they move between\u00a0those snapshots. By working out how far they move and how they move between two snapshots,\u00a0LiDAR Boost\u00a0can calculate both forward and angular velocities, which can be fed into the GNSS\/INS as an\u00a0additional\u00a0data source.<\/span>\u00a0<\/span><\/p>\n

    LiDAR Boost\u00a0is great for mapping activities taking place in GNSS-denied spaces like underground car parks. Compare the route mapped out by an INS without\u00a0LiDAR Boost, to the same route mapped using\u00a0the technology:<\/span>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

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    Precision data demands precision positioning<\/h5>\n\n\n
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    We h<\/span>ope this blog has been a good introduction to point clouds and why they matter for\u00a0<\/span>surveyors and autonomous navigation engineers.<\/span>\u00a0The key takeaway is that point cloud data needs\u00a0<\/span>accurate<\/span>\u00a0georeferencing\u00a0<\/span>in<\/span>\u00a0order to<\/span>\u00a0<\/span>deliver the most value \u2013 and that requires\u00a0<\/span>an accurate<\/span>\u00a0positioning solution. OXTS has a combination of hardware and software tools that enable mobile mappers to get\u00a0<\/span>accurate<\/span>\u00a0position data, even in environments where GNSS signal is weak or\u00a0<\/span>nonexistent<\/span>; working with us, you can maximise the value of your point cloud data.\u00a0<\/span><\/span><\/p>\n

     <\/p>\n

    If\u00a0<\/span>you\u2019d<\/span>\u00a0like to discuss<\/span>\u00a0how O<\/span>X<\/span>TS can help you integrate point clouds into your\u00a0<\/span>workflow, click below to get in touch.<\/span><\/span>\u00a0<\/span><\/p>\n\n <\/div>\n\n <\/div>\n <\/div>\n \n \n <\/div>\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

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