{"product_id":"resepi-gen-ii-os1-and-m2x-drone-lidar-systems","title":"RESEPI GEN-II OS1 and M2X Drone LiDAR Systems","description":"\u003cdiv class=\"mxgen2\"\u003e\n  \u003cstyle\u003e\n    .mxgen2 {\n      width: 100% !important;\n      max-width: 100% !important;\n      min-width: 0 !important;\n      margin: 0 !important;\n      padding: 0 !important;\n      color: #20262b;\n      font-family: inherit;\n      font-size: 16px;\n      line-height: 1.65;\n      overflow: visible !important;\n    }\n\n    .mxgen2,\n    .mxgen2 * {\n      box-sizing: border-box !important;\n    }\n\n    .mxgen2 * {\n      min-width: 0 !important;\n      max-width: 100% !important;\n      overflow-wrap: break-word;\n      word-break: normal;\n      hyphens: none;\n    }\n\n    .mxgen2 section,\n    .mxgen2 article,\n    .mxgen2 figure,\n    .mxgen2 div,\n    .mxgen2 dl,\n    .mxgen2 ul {\n      display: block !important;\n      width: 100% !important;\n      float: none !important;\n      clear: both 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#10293f;\n      border-radius: 10px;\n    }\n\n    .mxgen2__cta h2,\n    .mxgen2__cta p {\n      color: #ffffff;\n    }\n\n    .mxgen2__cta p {\n      color: rgba(255,255,255,0.86);\n    }\n\n    @media screen and (max-width: 480px) {\n      .mxgen2 {\n        font-size: 15px;\n      }\n\n      .mxgen2 h2 {\n        font-size: 26px;\n      }\n\n      .mxgen2 h3 {\n        font-size: 20px;\n      }\n\n      .mxgen2__hero,\n      .mxgen2__cta {\n        padding: 23px 18px !important;\n      }\n\n      .mxgen2__card,\n      .mxgen2__camera {\n        padding: 19px 17px !important;\n      }\n\n      .mxgen2__camera img {\n        width: 100% !important;\n      }\n    }\n  \u003c\/style\u003e\n\n  \u003c!-- INTRODUCTION: product images and Shopify variant selector remain in the native product section above this description --\u003e\n  \u003csection class=\"mxgen2__hero\"\u003e\n    \u003cspan class=\"mxgen2__eyebrow\"\u003eRESEPI GEN-II Sensor-Fusion LiDAR Systems\u003c\/span\u003e\n    \u003ch2\u003eAdvanced Drone LiDAR With 61 MP Sony Imaging\u003c\/h2\u003e\n    \u003cp\u003e\n      The RESEPI GEN-II OS1-ILX and M2X-ILX combine airborne LiDAR,\n      dual-antenna GNSS-aided inertial navigation, powerful onboard computing\n      and a Sony ILX-LR1 61 MP camera in configurable payloads for public\n      safety, emergency management and civil government mapping.\n    \u003c\/p\u003e\n    \u003cp\u003e\n      Both variants support real-time field checks and post-processed workflows\n      for crime and accident-scene documentation, tactical planning, disaster\n      assessment, search-area mapping, infrastructure capture, GIS, CAD,\n      photogrammetry and orthomosaic production. Choose the variant above based\n      on whether the mission prioritizes extremely high point throughput and a\n      broad vertical scan, or longer detection range, higher operating altitude\n      and tighter published system accuracy.\n    \u003c\/p\u003e\n\n    \u003cspan class=\"mxgen2__pill\"\u003eSony ILX-LR1 61 MP camera\u003c\/span\u003e\n    \u003cspan class=\"mxgen2__pill\"\u003eReal-time point-cloud visualization\u003c\/span\u003e\n    \u003cspan class=\"mxgen2__pill\"\u003eRTK and PPK workflows\u003c\/span\u003e\n    \u003cspan class=\"mxgen2__pill\"\u003eAerial, mobile and pedestrian mapping\u003c\/span\u003e\n\n    \u003ca class=\"mxgen2__button\" href=\"mailto:ops@maxsur.com?subject=RESEPI%20GEN-II%20OS1%20or%20M2X%20LiDAR%20Configuration\"\u003eRequest a Configured Quote\u003c\/a\u003e\n    \u003ca class=\"mxgen2__button mxgen2__button--outline\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003eCompare All Drone LiDAR Systems\u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- VARIANT GUIDE --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eSelect the Right Shopify Variant\u003c\/span\u003e\n      \u003ch2\u003eOS1-ILX or M2X-ILX?\u003c\/h2\u003e\n      \u003cp\u003e\n        The two GEN-II configurations share the same advanced positioning,\n        computing, Sony imaging and processing architecture. Their LiDAR\n        scanners are optimized for different collection priorities.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxgen2__card mxgen2__variant\"\u003e\n      \u003cspan class=\"mxgen2__variant-tag\"\u003eOS1-ILX Variant\u003c\/span\u003e\n      \u003ch3\u003eHigh Point Throughput and Broad Vertical Coverage\u003c\/h3\u003e\n      \u003cp\u003e\n        The Ouster OS1-64 REV7 configuration uses 64 laser channels and\n        produces up to 2.621 million measurements per second in dual-return\n        operation. Its 45-degree vertical field of view is well suited to\n        efficiently capturing complex geometry, vertical structures and dense\n        scene detail.\n      \u003c\/p\u003e\n      \u003cul class=\"mxgen2__list\"\u003e\n        \u003cli\u003e64 laser channels and two returns\u003c\/li\u003e\n        \u003cli\u003e2,621k measurements per second in dual-return mode\u003c\/li\u003e\n        \u003cli\u003e45° vertical field of view and 360° horizontal coverage\u003c\/li\u003e\n        \u003cli\u003eUp to 75 m recommended AGL\u003c\/li\u003e\n        \u003cli\u003ePublished system accuracy of 3–5 cm under stated test conditions\u003c\/li\u003e\n        \u003cli\u003eStrong fit for structures, campuses, corridors, tactical sites and dense local-area mapping\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card mxgen2__variant mxgen2__variant--m2x\"\u003e\n      \u003cspan class=\"mxgen2__variant-tag\"\u003eM2X-ILX Variant\u003c\/span\u003e\n      \u003ch3\u003eLonger Range, Higher Altitude and Triple Returns\u003c\/h3\u003e\n      \u003cp\u003e\n        The enhanced XT-32M2X configuration extends detection range to as much\n        as 300 m under specified conditions, supports up to three returns and\n        carries a recommended operating altitude of up to 150 m. It is the\n        stronger choice when coverage area, vegetation penetration and tighter\n        published system accuracy are the priority.\n      \u003c\/p\u003e\n      \u003cul class=\"mxgen2__list\"\u003e\n        \u003cli\u003e32 laser channels and up to three returns\u003c\/li\u003e\n        \u003cli\u003eUp to 1,920k measurements per second in triple-return mode\u003c\/li\u003e\n        \u003cli\u003e40.3° vertical field of view and 360° horizontal coverage\u003c\/li\u003e\n        \u003cli\u003eUp to 150 m recommended AGL\u003c\/li\u003e\n        \u003cli\u003ePublished system accuracy of 2–3 cm under stated test conditions\u003c\/li\u003e\n        \u003cli\u003eStrong fit for wide-area scenes, disaster assessment, wooded searches, corridors and civil mapping\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003cdiv class=\"mxgen2__callout\"\u003e\n      \u003cp\u003e\n        \u003cstrong\u003eConfiguration guidance:\u003c\/strong\u003e OS1-ILX emphasizes point\n        throughput and 64-channel scene density. M2X-ILX emphasizes range,\n        altitude, triple-return collection and tighter published system-level\n        accuracy. MAXSUR can help match the variant, aircraft, mount, software\n        and control strategy to the required deliverable.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- SHARED SYSTEM DETAILS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eShared GEN-II Architecture\u003c\/span\u003e\n      \u003ch2\u003eA Complete Mapping Payload, Not Just a LiDAR Scanner\u003c\/h2\u003e\n      \u003cp\u003e\n        Both variants integrate sensing, positioning, image capture, onboard\n        computing and processing support into a field-deployable 1.7 kg system.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__stat-list\"\u003e\n      \u003cdiv class=\"mxgen2__stat\"\u003e\n\u003cstrong\u003e1.7 kg\u003c\/strong\u003e\u003cspan\u003eComplete payload weight for either variant\u003c\/span\u003e\n\u003c\/div\u003e\n      \u003cdiv class=\"mxgen2__stat\"\u003e\n\u003cstrong\u003e61 MP\u003c\/strong\u003e\u003cspan\u003eSony ILX-LR1 full-frame imaging for colorization and image-based deliverables\u003c\/span\u003e\n\u003c\/div\u003e\n      \u003cdiv class=\"mxgen2__stat\"\u003e\n\u003cstrong\u003e512 GB\u003c\/strong\u003e\u003cspan\u003eInternal SSD storage\u003c\/span\u003e\n\u003c\/div\u003e\n      \u003cdiv class=\"mxgen2__stat\"\u003e\n\u003cstrong\u003e33 minutes\u003c\/strong\u003e\u003cspan\u003ePublished maximum flight time on DJI M300 test configuration\u003c\/span\u003e\n\u003c\/div\u003e\n      \u003cdiv class=\"mxgen2__stat\"\u003e\n\u003cstrong\u003eHexacore\u003c\/strong\u003e\u003cspan\u003eOnboard computer with 8 GB DDR4 RAM and 16 GB eMMC\u003c\/span\u003e\n\u003c\/div\u003e\n      \u003cdiv class=\"mxgen2__stat\"\u003e\n\u003cstrong\u003eRTK + PPK\u003c\/strong\u003e\u003cspan\u003eDual-antenna GNSS-aided inertial navigation workflows\u003c\/span\u003e\n\u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- APPLICATION POINT CLOUD --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxgen2__media\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Resepi-GENII-OS1-and-M2X-ILX-Point-Cloud-Image-of-Electric-Utility-Lines.jpg?v=1783898967\" alt=\"RESEPI GEN-II drone LiDAR point cloud of utility lines, terrain and vegetation\" width=\"1200\" height=\"900\" loading=\"lazy\"\u003e\n      \u003cfigcaption class=\"mxgen2__caption\"\u003eGEN-II point-cloud collection can preserve terrain, vegetation, buildings and vertical infrastructure within one georeferenced dataset.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eBuilt Around Government Missions\u003c\/span\u003e\n      \u003ch2\u003eTranslate Sensor Performance Into Operational Data\u003c\/h2\u003e\n      \u003cp\u003e\n        GEN-II supports data collection where conventional ground-only methods\n        can be too slow, incomplete or hazardous. The result is a measurable 3D\n        record that can be reviewed, processed and exported into established\n        public-sector geospatial workflows.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxgen2__card\"\u003e\n      \u003ch3\u003ePublic Safety, Forensics and Tactical Planning\u003c\/h3\u003e\n      \u003cp\u003e\n        Capture broad scene context while reducing the time personnel spend in\n        traffic lanes, unstable terrain, hazardous perimeters or large outdoor\n        scenes.\n      \u003c\/p\u003e\n      \u003cul class=\"mxgen2__list\"\u003e\n        \u003cli\u003eMajor crime and accident-scene documentation\u003c\/li\u003e\n        \u003cli\u003eMeasured point clouds for reconstruction and evidentiary visualization\u003c\/li\u003e\n        \u003cli\u003eIngress, egress, perimeter and line-of-sight planning\u003c\/li\u003e\n        \u003cli\u003eCampus, correctional, critical-site and special-event mapping\u003c\/li\u003e\n        \u003cli\u003eColorized point clouds, orthomosaics and photogrammetry products\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card\"\u003e\n      \u003ch3\u003eEmergency Management and Search Operations\u003c\/h3\u003e\n      \u003cp\u003e\n        Document conditions over areas that may be changing quickly or remain\n        difficult to access safely from the ground.\n      \u003c\/p\u003e\n      \u003cul class=\"mxgen2__list\"\u003e\n        \u003cli\u003eSearch-and-rescue terrain and vegetation mapping\u003c\/li\u003e\n        \u003cli\u003eFlood, storm, fire and structural damage assessment\u003c\/li\u003e\n        \u003cli\u003eDebris, access-route and staging-area documentation\u003c\/li\u003e\n        \u003cli\u003ePre-incident planning and post-event change comparison\u003c\/li\u003e\n        \u003cli\u003eWide-area mapping for unified command and recovery planning\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card\"\u003e\n      \u003ch3\u003eCivil Government, Engineering, GIS and CAD\u003c\/h3\u003e\n      \u003cp\u003e\n        Build detailed geospatial datasets for engineering, public works,\n        transportation, utilities, planning and asset-management teams.\n      \u003c\/p\u003e\n      \u003cul class=\"mxgen2__list\"\u003e\n        \u003cli\u003eRoadway, corridor and right-of-way mapping\u003c\/li\u003e\n        \u003cli\u003eBuildings, facades, poles, conductors and other vertical assets\u003c\/li\u003e\n        \u003cli\u003eSurface models, elevation products and volumetric analysis\u003c\/li\u003e\n        \u003cli\u003eGIS base mapping and CAD-ready point-cloud workflows\u003c\/li\u003e\n        \u003cli\u003eRepeat capture for construction progress and asset change detection\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- MULTI-MODE OPERATIONS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eOne Sensor Platform, Multiple Collection Methods\u003c\/span\u003e\n      \u003ch2\u003eMove Beyond Aerial Mapping When the Mission Requires It\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxgen2__step\"\u003e\n      \u003cspan class=\"mxgen2__step-number\"\u003e1\u003c\/span\u003e\n      \u003ch3\u003eAirborne Drone LiDAR\u003c\/h3\u003e\n      \u003cp\u003e\n        Use a compatible enterprise UAV to capture large scenes, corridors,\n        terrain, vegetation and infrastructure from above with synchronized\n        LiDAR, imagery and GNSS\/INS data.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__step\"\u003e\n      \u003cspan class=\"mxgen2__step-number\"\u003e2\u003c\/span\u003e\n      \u003ch3\u003ePedestrian and Backpack SLAM\u003c\/h3\u003e\n      \u003cp\u003e\n        Reconfigure the payload for pedestrian mapping where overhead flight\n        is impractical, including interiors, covered areas, narrow passages or\n        spaces requiring a ground-level perspective.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__step\"\u003e\n      \u003cspan class=\"mxgen2__step-number\"\u003e3\u003c\/span\u003e\n      \u003ch3\u003eVehicle and Mobile Mapping\u003c\/h3\u003e\n      \u003cp\u003e\n        Integrate GEN-II with mobile platforms and supported aiding inputs for\n        roads, campuses, transportation assets, public works inventories and\n        repeatable corridor collection.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__step\"\u003e\n      \u003cspan class=\"mxgen2__step-number\"\u003e4\u003c\/span\u003e\n      \u003ch3\u003eRobotics and Custom Integration\u003c\/h3\u003e\n      \u003cp\u003e\n        Use external camera, LiDAR, GNSS, wheel-speed, odometer and other\n        integration support to build specialized robotic or multi-sensor\n        government mapping systems.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- SONY CAMERA --\u003e\n  \u003csection class=\"mxgen2__camera\"\u003e\n    \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Sony-ILX-LR1-Drone-Crime-Scene-Payload-for-LiDAR-and-Photogrammetry-Missions.png?v=1783896640\" alt=\"Sony ILX-LR1 61 megapixel camera for RESEPI GEN-II LiDAR colorization, orthomosaic and photogrammetry missions\" width=\"1000\" height=\"800\" loading=\"lazy\"\u003e\n\n    \u003cspan class=\"mxgen2__eyebrow\"\u003eIncluded Sony ILX-LR1 Camera\u003c\/span\u003e\n    \u003ch2\u003eHigh-Resolution Imagery for Colorization and Photogrammetry\u003c\/h2\u003e\n    \u003cp\u003e\n      Both GEN-II variants pair the LiDAR scanner with a Sony ILX-LR1 61 MP\n      full-frame camera. The integrated 18 mm lens configuration provides a\n      published 100-degree field of view and supports synchronized image\n      capture alongside the LiDAR and navigation data.\n    \u003c\/p\u003e\n    \u003cp\u003e\n      For engineering, GIS and crime or accident-scene documentation, the\n      camera adds much more than attractive color. High-resolution imagery can\n      improve feature identification within colorized point clouds and support\n      associated orthomosaic and photogrammetry deliverables when the mission\n      is planned, controlled and processed appropriately.\n    \u003c\/p\u003e\n\n    \u003cdiv class=\"mxgen2__callout\"\u003e\n      \u003cp\u003e\n        \u003cstrong\u003ePublished camera configuration:\u003c\/strong\u003e 61 MP Sony ILX-LR1,\n        fixed manual-focus 18 mm lens, one-second maximum trigger interval,\n        100° field of view and an estimated 2 cm GSD at 50 m AGL under the\n        manufacturer's stated configuration.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- FIELD WORKFLOW --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eRESEPI GEN-II Processing Workflow\u003c\/span\u003e\n      \u003ch2\u003eCheck the Mission in the Field, Then Build the Deliverable\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxgen2__feature\"\u003e\n      \u003ch3\u003eReal-Time Visualization and Field Checks\u003c\/h3\u003e\n      \u003cp\u003e\n        The GEN-II onboard computer supports real-time point-cloud\n        visualization and field verification, helping operators identify\n        missing coverage before aircraft, personnel and scene-control resources\n        leave the location.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__feature\"\u003e\n      \u003ch3\u003ePCMasterPro Processing\u003c\/h3\u003e\n      \u003cp\u003e\n        PCMasterPro supports pre-processing, post-processing, coordinate-system\n        transformation, batch processing and noise filtering for repeatable\n        aerial and mobile mapping workflows.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__feature\"\u003e\n      \u003ch3\u003eSLAM and Strip Alignment\u003c\/h3\u003e\n      \u003cp\u003e\n        Kudan-powered SLAM expands pedestrian and mobile collection options,\n        while BayesMap-powered strip alignment helps refine overlapping flight\n        lines and improve the consistency of the final point cloud.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__feature\"\u003e\n      \u003ch3\u003eExpandable Sensor Integration\u003c\/h3\u003e\n      \u003cp\u003e\n        MAVLink, DJI Payload SDK and external sensor support allow GEN-II to\n        become part of a larger mission system rather than remaining an\n        isolated payload.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- RECOMMENDED AIRCRAFT --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxgen2__media\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Drone-LiDAR-for-Crime-Scenes-with-Inspired-Flight-IF1200-and-Scanner.jpg?v=1783890157\" alt=\"Inspired Flight enterprise drone configured with an airborne LiDAR scanner\" width=\"1400\" height=\"1050\" loading=\"lazy\"\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eRecommended Government Drone Platforms\u003c\/span\u003e\n      \u003ch2\u003eBuild a Complete GEN-II Drone LiDAR System\u003c\/h2\u003e\n      \u003cp\u003e\n        MAXSUR can configure the aircraft, payload mount, communications,\n        positioning workflow, processing software, mapping targets, training\n        and support around the agency's deliverables.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxgen2__card\"\u003e\n      \u003ch3\u003eInspired Flight IF800 Tomcat\u003c\/h3\u003e\n      \u003cp\u003e\n        A deployable medium-lift platform suited to agencies that need a\n        practical balance of portability, professional payload capability and\n        field endurance.\n      \u003c\/p\u003e\n      \u003ca href=\"https:\/\/www.maxsur.com\/collections\/drones\/products\/if800-tomcat-medium-lift-drone\"\u003e\u003cstrong\u003eView the Inspired Flight IF800 Tomcat →\u003c\/strong\u003e\u003c\/a\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card\"\u003e\n      \u003ch3\u003eInspired Flight IF1200\u003c\/h3\u003e\n      \u003cp\u003e\n        A heavy-lift platform offering additional payload, power and\n        integration margin for advanced sensor packages and specialized\n        government missions.\n      \u003c\/p\u003e\n      \u003ca href=\"https:\/\/www.maxsur.com\/collections\/drones\/products\/if1200-heavy-lift-hexacopter\"\u003e\u003cstrong\u003eView the Inspired Flight IF1200 →\u003c\/strong\u003e\u003c\/a\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- SPECIFICATIONS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eTechnical Specifications\u003c\/span\u003e\n      \u003ch2\u003eCompare the GEN-II OS1-ILX and M2X-ILX Variants\u003c\/h2\u003e\n      \u003cp\u003e\n        Use the Shopify variant selector in the product-purchase area to choose\n        a configuration. The downloadable manufacturer datasheets are placed\n        directly beside each specification set below.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003c!-- OS1 SPECIFICATIONS --\u003e\n    \u003cdiv class=\"mxgen2__spec-download\"\u003e\n      \u003ch3\u003eRESEPI GEN-II OS1-ILX Datasheet\u003c\/h3\u003e\n      \u003cp\u003eDownload the complete manufacturer specification sheet for the 64-channel Ouster OS1-64 REV7 configuration.\u003c\/p\u003e\n      \u003ca class=\"mxgen2__button mxgen2__button--blue\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI_GEN-II_OS1-ILX_Datasheet_rev-1.6_Jul_1_2026-Available-at-MAXSUR.pdf?v=1783897932\" target=\"_blank\" rel=\"noopener\"\u003eDownload the OS1-ILX Datasheet\u003c\/a\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eOS1-ILX System\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePublished system accuracy\u003c\/dt\u003e\n\u003cdd\u003e3–5 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePrecision\u003c\/dt\u003e\n\u003cdd\u003e4–6 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePrecision after one-sigma noise removal\u003c\/dt\u003e\n\u003cdd\u003e2–4 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eRecommended AGL\u003c\/dt\u003e\n\u003cdd\u003eUp to 75 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eWeight\u003c\/dt\u003e\n\u003cdd\u003e1.7 kg\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eDimensions\u003c\/dt\u003e\n\u003cdd\u003e21.3 × 17.8 × 13 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eMaximum published flight time\u003c\/dt\u003e\n\u003cdd\u003e33 minutes on DJI M300 test configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eInternal storage\u003c\/dt\u003e\n\u003cdd\u003e512 GB SSD\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eSystem computer\u003c\/dt\u003e\n\u003cdd\u003eHexacore, 8 GB DDR4 RAM, 16 GB eMMC\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eOperational voltage\u003c\/dt\u003e\n\u003cdd\u003e9–50 V\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePower consumption\u003c\/dt\u003e\n\u003cdd\u003e55 W\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eOS1-ILX LiDAR Scanner\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eScanner\u003c\/dt\u003e\n\u003cdd\u003eOuster OS1-64 REV7\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eLaser range capability\u003c\/dt\u003e\n\u003cdd\u003e90 m at 10% reflectivity on all channels; 0.5 to 200 m in stated operating mode\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eRange accuracy\u003c\/dt\u003e\n\u003cdd\u003e±2.5 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eHorizontal field of view\u003c\/dt\u003e\n\u003cdd\u003e360°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eVertical field of view\u003c\/dt\u003e\n\u003cdd\u003e45°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eVertical scan angle\u003c\/dt\u003e\n\u003cdd\u003e-22.5° to +22.5°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eBeam divergence\u003c\/dt\u003e\n\u003cdd\u003e0.18° horizontal; 0.18° vertical, varying by measurement range\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eLaser channels\u003c\/dt\u003e\n\u003cdd\u003e64\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eNumber of returns\u003c\/dt\u003e\n\u003cdd\u003e2\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePulse rate\u003c\/dt\u003e\n\u003cdd\u003e2,621k measurements per second in dual-return mode\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003c!-- M2X SPECIFICATIONS --\u003e\n    \u003cdiv class=\"mxgen2__spec-download\"\u003e\n      \u003ch3\u003eRESEPI GEN-II M2X-ILX Datasheet\u003c\/h3\u003e\n      \u003cp\u003eDownload the complete manufacturer specification sheet for the enhanced XT-32M2X configuration.\u003c\/p\u003e\n      \u003ca class=\"mxgen2__button mxgen2__button--blue\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI_GEN-II_M2X-ILX_Datasheet_rev-1.7_Jul_1_2026-Available-At-MAXSUR.pdf?v=1783898536\" target=\"_blank\" rel=\"noopener\"\u003eDownload the M2X-ILX Datasheet\u003c\/a\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eM2X-ILX System\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePublished system accuracy\u003c\/dt\u003e\n\u003cdd\u003e2–3 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePrecision\u003c\/dt\u003e\n\u003cdd\u003e2–4 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePrecision after one-sigma noise removal\u003c\/dt\u003e\n\u003cdd\u003e1.5–2.5 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eRecommended AGL\u003c\/dt\u003e\n\u003cdd\u003eUp to 150 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eWeight\u003c\/dt\u003e\n\u003cdd\u003e1.7 kg\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eDimensions\u003c\/dt\u003e\n\u003cdd\u003e21.6 × 17.8 × 13 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eMaximum published flight time\u003c\/dt\u003e\n\u003cdd\u003e33 minutes on DJI M300 test configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eInternal storage\u003c\/dt\u003e\n\u003cdd\u003e512 GB SSD\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eSystem computer\u003c\/dt\u003e\n\u003cdd\u003eHexacore, 8 GB DDR4 RAM, 16 GB eMMC\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eOperational voltage\u003c\/dt\u003e\n\u003cdd\u003e9–50 V\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePower consumption\u003c\/dt\u003e\n\u003cdd\u003e40 W\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eM2X-ILX LiDAR Scanner\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eScanner\u003c\/dt\u003e\n\u003cdd\u003eEnhanced XT-32M2X\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eLaser range capability\u003c\/dt\u003e\n\u003cdd\u003e80 m at 10% reflectivity on all channels; 0.05 to 300 m under specified conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eRange accuracy\u003c\/dt\u003e\n\u003cdd\u003e±1 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eHorizontal field of view\u003c\/dt\u003e\n\u003cdd\u003e360°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eVertical field of view\u003c\/dt\u003e\n\u003cdd\u003e40.3°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eVertical scan angle\u003c\/dt\u003e\n\u003cdd\u003e-20.8° to +19.5°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eBeam divergence\u003c\/dt\u003e\n\u003cdd\u003e0.056° horizontal; 0.1° vertical, varying by measurement range\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eLaser channels\u003c\/dt\u003e\n\u003cdd\u003e32\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eNumber of returns\u003c\/dt\u003e\n\u003cdd\u003e3\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePulse rate\u003c\/dt\u003e\n\u003cdd\u003e640k\/s single return; 1,280k\/s dual return; 1,920k\/s triple return\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003c!-- SHARED CAMERA \/ INS \/ SOFTWARE --\u003e\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eShared Sony ILX-LR1 Camera\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eModel\u003c\/dt\u003e\n\u003cdd\u003eSony ILX-LR1\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eResolution\u003c\/dt\u003e\n\u003cdd\u003e61 MP\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eLens\u003c\/dt\u003e\n\u003cdd\u003eFixed manual-focus 18 mm lens in published configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eMaximum trigger interval\u003c\/dt\u003e\n\u003cdd\u003e1 second\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eField of view\u003c\/dt\u003e\n\u003cdd\u003e100°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eEstimated GSD\u003c\/dt\u003e\n\u003cdd\u003e2 cm at 50 m AGL in published configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eShared GPS-Aided Inertial Navigation\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eIMU\u003c\/dt\u003e\n\u003cdd\u003eInertial Labs KERNEL-210 tactical-grade inertial measurement unit\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eGNSS receiver\u003c\/dt\u003e\n\u003cdd\u003eNovAtel OEM7720\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eConstellations\u003c\/dt\u003e\n\u003cdd\u003eGPS, GLONASS, Galileo, BeiDou, QZSS, NavIC\/IRNSS, SBAS and available L-Band\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eFrequencies\u003c\/dt\u003e\n\u003cdd\u003eL1, L2 and L5, dependent on receiver configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eOperation modes\u003c\/dt\u003e\n\u003cdd\u003eRTK and PPK\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eNavigation algorithm\u003c\/dt\u003e\n\u003cdd\u003eExtended Kalman Filter\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eOutput rates\u003c\/dt\u003e\n\u003cdd\u003eUp to 200 Hz INS; up to 2,000 Hz IMU\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePitch \/ roll accuracy\u003c\/dt\u003e\n\u003cdd\u003e0.03° RTK; 0.004° PPK under stated conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eHeading accuracy\u003c\/dt\u003e\n\u003cdd\u003e0.08° RTK; 0.02° PPK under stated conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eVelocity accuracy\u003c\/dt\u003e\n\u003cdd\u003eLess than 0.03 m\/s\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePosition accuracy\u003c\/dt\u003e\n\u003cdd\u003e1 cm + 1 ppm RTK; 0.5 cm PPK under stated conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxgen2__spec-group\"\u003e\n      \u003ch3\u003eShared Integration and PCMasterPro Support\u003c\/h3\u003e\n      \u003cdl class=\"mxgen2__spec-list\"\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eExternal camera support\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eExternal LiDAR support\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eExternal GNSS receiver support\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eOdometer or wheel-speed sensor support\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eMAVLink and DJI Payload SDK capability\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eField checks\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePre-processing\u003c\/dt\u003e\n\u003cdd\u003eYes\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003ePost-processing\u003c\/dt\u003e\n\u003cdd\u003eSupported\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eSLAM\u003c\/dt\u003e\n\u003cdd\u003eYes, powered by Kudan\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eStrip alignment\u003c\/dt\u003e\n\u003cdd\u003eYes, powered by BayesMap\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxgen2__spec-row\"\u003e\n\u003cdt\u003eAdditional software functions\u003c\/dt\u003e\n\u003cdd\u003eCoordinate-system transformation, batch processing, open architecture, noise filtering and additional workflow tools\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cp class=\"mxgen2__note\"\u003e\n      Published system accuracy and precision values are based on the\n      manufacturer's stated single-pass aerial test conditions. Range,\n      accuracy, point density, endurance and final deliverable quality vary\n      with operating mode, target reflectivity, altitude, speed, overlap,\n      atmosphere, aircraft, calibration, control strategy and processing.\n      Aircraft operations must remain within applicable regulations, waivers,\n      manufacturer limitations and agency policy.\n    \u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- ADAPTERS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eField-Swappable Payload Integration\u003c\/span\u003e\n      \u003ch2\u003eMount GEN-II to the Right Aircraft and Mission Platform\u003c\/h2\u003e\n      \u003cp\u003e\n        RESEPI adapters support mechanical integration, power and data\n        communication across several professional aircraft families. Final\n        compatibility, balance, endurance and communications should be verified\n        for the selected GEN-II variant and aircraft.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxgen2__card mxgen2__adapter\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/DJI-LiDAR-skyport-adapter-top.jpg?v=1783887977\" alt=\"DJI Skyport adapter for RESEPI GEN-II LiDAR payload\" width=\"700\" height=\"525\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__adapter-copy\"\u003e\n        \u003ch3\u003eDJI Skyport Interface\u003c\/h3\u003e\n        \u003cp\u003eDesigned for compatible DJI enterprise aircraft such as the M300 and M350, supporting payload mounting, power and data transmission.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card mxgen2__adapter\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Freefly-LiDAR-adapter-dovetail.jpg?v=1783887950\" alt=\"Freefly Smart Dovetail adapter for RESEPI GEN-II LiDAR payload\" width=\"700\" height=\"525\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__adapter-copy\"\u003e\n        \u003ch3\u003eFreefly Smart Dovetail\u003c\/h3\u003e\n        \u003cp\u003eSupports the Freefly Astro and other aircraft using the industry-adopted Smart Dovetail interface for mechanical integration, power and data.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card mxgen2__adapter\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/WISPR-Skyscout-drone-LiDAR-Adapter-Top.jpg?v=1783887826\" alt=\"WISPR SkyScout adapter for RESEPI GEN-II LiDAR payload\" width=\"700\" height=\"525\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__adapter-copy\"\u003e\n        \u003ch3\u003eWISPR SkyScout Interface\u003c\/h3\u003e\n        \u003cp\u003eA platform-specific interface supporting payload power and data communication for compatible WISPR SkyScout configurations.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxgen2__card mxgen2__adapter\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/WISPR-Skyscout-LiDAR-Adapter-w-FPV.jpg?v=1783887733\" alt=\"WISPR SkyScout RESEPI LiDAR adapter with FPV camera\" width=\"700\" height=\"525\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__adapter-copy\"\u003e\n        \u003ch3\u003eWISPR SkyScout Interface With FPV\u003c\/h3\u003e\n        \u003cp\u003eAdds an optional FPV camera integrated with the aircraft controller to improve payload awareness, operator visibility and in-flight quality control.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/article\u003e\n\n    \u003cdiv class=\"mxgen2__callout\"\u003e\n      \u003cp\u003e\n        \u003cstrong\u003eIntegration note:\u003c\/strong\u003e Aircraft compatibility, center of\n        gravity, available power, flight endurance, mounting interface and data\n        communication must be verified for the final variant and aircraft\n        combination before deployment.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- RELATED RESOURCES --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxgen2__section-head\"\u003e\n      \u003cspan class=\"mxgen2__eyebrow\"\u003eComplete the Mapping Program\u003c\/span\u003e\n      \u003ch2\u003eRelated Drone LiDAR Resources\u003c\/h2\u003e\n      \u003cp\u003e\n        Pair the payload with the right aircraft, field-control tools and\n        training to build a repeatable public-sector mapping capability.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003ca class=\"mxgen2__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Drone-LiDAR-for-Crime-Scene-Mapping.jpg?v=1783441385\" alt=\"Drone LiDAR systems for crime scene, emergency response and government mapping\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__link-copy\"\u003e\n        \u003ch3\u003eAll Drone LiDAR Systems\u003c\/h3\u003e\n        \u003cp\u003eCompare payloads and configurations for public safety, emergency response, GIS, engineering and inspection missions.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n\n    \u003ca class=\"mxgen2__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/mapping-targets\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/LiDAR-targets-for-crime-scene-forensics.jpg?v=1783441142\" alt=\"LiDAR and photogrammetry mapping targets for forensic and engineering control\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__link-copy\"\u003e\n        \u003ch3\u003eSurvey and Mapping Targets\u003c\/h3\u003e\n        \u003cp\u003eEstablish visible control, improve repeatability and connect aerial data with ground survey, engineering and forensic workflows.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n\n    \u003ca class=\"mxgen2__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/uas-training-and-program-support\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/UAS-Training-and-Program-Support-for-Law-Enforcement.jpg?v=1783442300\" alt=\"UAS training and program support for law enforcement and government agencies\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxgen2__link-copy\"\u003e\n        \u003ch3\u003eUAS Training and Program Support\u003c\/h3\u003e\n        \u003cp\u003eDevelop pilot proficiency, mapping procedures, documentation and a sustainable operational program.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- FINAL CTA --\u003e\n  \u003csection class=\"mxgen2__cta\"\u003e\n    \u003cspan class=\"mxgen2__eyebrow\"\u003eConfigured and Supported by MAXSUR\u003c\/span\u003e\n    \u003ch2\u003eBuild the GEN-II System Around the Required Deliverable\u003c\/h2\u003e\n    \u003cp\u003e\n      Tell us whether the priority is crime-scene documentation, accident\n      reconstruction, tactical planning, search and rescue, disaster\n      assessment, utilities, GIS, CAD, engineering, photogrammetry or mobile\n      SLAM. MAXSUR can help select the OS1-ILX or M2X-ILX variant, aircraft,\n      adapter, control strategy, processing workflow, mapping targets, training\n      and support package required to turn the payload into an operational\n      capability.\n    \u003c\/p\u003e\n\n    \u003ca class=\"mxgen2__button\" href=\"mailto:ops@maxsur.com?subject=MAXSUR%20RESEPI%20GEN-II%20LiDAR%20System\"\u003eContact MAXSUR\u003c\/a\u003e\n    \u003ca class=\"mxgen2__button mxgen2__button--outline\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003eExplore All Drone LiDAR\u003c\/a\u003e\n  \u003c\/section\u003e\n\u003c\/div\u003e","brand":"MAXSUR","offers":[{"title":"OS1","offer_id":45990067273762,"sku":"IL-PRD250682-001","price":51500.0,"currency_code":"USD","in_stock":true},{"title":"M2X","offer_id":45990067306530,"sku":"IL-PRD250681-001","price":45500.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-GEN-II-OS1-and-M2X-ILX-Drone-LiDAR-Scanner-for-Crime-Scene-Mapping.jpg?v=1783899696","url":"https:\/\/www.maxsur.com\/products\/resepi-gen-ii-os1-and-m2x-drone-lidar-systems","provider":"MAXSUR","version":"1.0","type":"link"}