{"product_id":"yahboom-ai-view-depth-camera","title":"Yahboom AI VIEW Binocular Structured Light 3D Depth Camera for ROS1\/ROS2 Robots, USB3.0 Type‑C RGBD","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eThe Yahboom AI VIEW is a binocular structured light 3D depth camera for ROS robot development. It combines binocular vision with structured light projection to calculate depth via left\/right image matching and triangulation, supporting 3D reconstruction and depth sensing in complex environments. The compact body size is listed as 68.3 × 25.3 × 19.0 mm, with a measurement range of 0.25–2.5 m and resistance to strong light for indoor use scenarios.\u003c\/p\u003e\u003ch2\u003eKey Features\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eBinocular structured light depth sensing; ranging principle: active binocular stereo vision\u003c\/li\u003e\n\u003cli\u003eROS support: ROS1 \u0026amp; ROS2; compatible with ROS1\/ROS2 systems and SDK support is noted\u003c\/li\u003e\n\u003cli\u003eBuilt-in depth engine chip: MX6000\u003c\/li\u003e\n\u003cli\u003eSmaller blind area: as low as 0.25 m (close-range measurement; suitable for robot end effector positioning)\u003c\/li\u003e\n\u003cli\u003eAnti-glare capability (strong-light resistance); usage note: “Please use it in indoor”\u003c\/li\u003e\n\u003cli\u003eCross-platform operating systems listed: Android \/ Linux \/ Windows8\/10\u003c\/li\u003e\n\u003cli\u003eExample platforms and scenarios shown: Raspberry Pi, Jetson, PC, programming education, robot, 3D face recognition, 3D object measurement, sensory games, smart devices\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eSpecifications\u003c\/h2\u003e\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003eProduct name\u003c\/td\u003e\n\u003ctd\u003eAI VIEW\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eModel\u003c\/td\u003e\n\u003ctd\u003eAstra SV1301S U3\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eBaseline\u003c\/td\u003e\n\u003ctd\u003e40 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eRanging principle\u003c\/td\u003e\n\u003ctd\u003eActive binocular stereo vision\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDepth range\u003c\/td\u003e\n\u003ctd\u003e0.25–2.5 m\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eRelative accuracy\u003c\/td\u003e\n\u003ctd\u003e±5 mm @ 1000 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAbsolute accuracy (multi-distance calibration not enabled)\u003c\/td\u003e\n\u003ctd\u003e±4 mm @ 200 mm; ±20 mm @ 900 mm; ±80 mm @ 2500 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAbsolute accuracy (multi-distance calibration enabled)\u003c\/td\u003e\n\u003ctd\u003e±4 mm @ 200 mm; ±14 mm @ 900 mm; ±60 mm @ 2500 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower consumption (typical)\u003c\/td\u003e\n\u003ctd\u003eAverage 2.2 W; Standby 0.9 W; Peak 5 W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower note\u003c\/td\u003e\n\u003ctd\u003eUSB2.0 maximum drive current must reach 1 A; depth 640 × 400 @ 60 FPS mode average power consumption 2.9 W\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDepth map resolution\u003c\/td\u003e\n\u003ctd\u003eUSB2.0 mode: 1280 × 800 @ 7 FPS; 640 × 400 @ 30 FPS\u003cbr\u003eUSB3.0 mode: 1280 × 800 @ 30 FPS; 640 × 400 @ 60 FPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eColor circle resolution\u003c\/td\u003e\n\u003ctd\u003eUSB2.0 mode: 1280 × 720 @ 7 FPS; 640 × 480 @ 30 FPS\u003cbr\u003eUSB3.0 mode: 1920 × 1080 @ 30 FPS; 1280 × 720 @ 30 FPS; 640 × 480 @ 30 FPS; 640 × 480 @ 60 FPS\u003cbr\u003e5M (still photo)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFrame rate\u003c\/td\u003e\n\u003ctd\u003eFrame rate dynamic adjustment\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDepth FOV\u003c\/td\u003e\n\u003ctd\u003eH67.9° V45.3° D78° ±3°\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eColor FOV\u003c\/td\u003e\n\u003ctd\u003eH71.5° V56.7° D84°\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDepth engine\u003c\/td\u003e\n\u003ctd\u003eMX6000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eData transmission\u003c\/td\u003e\n\u003ctd\u003eUSB3.0 Type-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower supply mode\u003c\/td\u003e\n\u003ctd\u003eUSB3.0 Type-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSupported operating systems\u003c\/td\u003e\n\u003ctd\u003eAndroid \/ Linux \/ Windows8\/10\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eROS support\u003c\/td\u003e\n\u003ctd\u003eROS1 \u0026amp; ROS2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOperating temperature\u003c\/td\u003e\n\u003ctd\u003e10°C to 40°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eApplicable scenarios (listed)\u003c\/td\u003e\n\u003ctd\u003eIndoor\u003cbr\u003eIndoor\/Outdoor (cloudy)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSafety (listed)\u003c\/td\u003e\n\u003ctd\u003eClass1 Laser\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOverall size (listed)\u003c\/td\u003e\n\u003ctd\u003eLength 68.3 mm; Width 25.25 mm; Thickness 19 mm\u003cbr\u003eAlso listed: 65.3 mm × 22.5 mm × 12.3 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (listed)\u003c\/td\u003e\n\u003ctd\u003e45.7 g\u003cbr\u003eAlso listed: 29.2 g\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMechanical drawing notes (unit: mm)\u003c\/td\u003e\n\u003ctd\u003eFront: 68.30 (W) × 25.25 (H); side thickness 19; mounting note: M3 threaded hole; additional drawing dimensions shown: 59.90, 45, 17\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\u003ch2\u003eSoftware \/ SDK Notes (as listed)\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e“[SDK] Provide better RGBD camera development experience” (Orbbec SDK): cross-platform (Windows, Android, Linux) for structured light, binocular, iToF and other 3D sensing cameras\u003c\/li\u003e\n\u003cli\u003eFunctions listed: hardware setting orientation and control; access\/control\/data reading of sensors; frame synchronization and alignment control; point cloud data acquisition; filtering and other algorithm capabilities; support for different systems and wrappers; display tool Orbbec Viewer\u003c\/li\u003e\n\u003cli\u003eViewer note: supports switching between Chinese and English\u003c\/li\u003e\n\u003cli\u003eBasic functions listed: view device information; obtain basic data streams; perform device control\u003c\/li\u003e\n\u003cli\u003eAdvanced functions listed: data frame synchronization and alignment; obtain point cloud data; data recording and playback\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eOptional Accessories\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eOptional angle-adjustable bracket for robot: 120° adjustable angle (Up 30°, Down 90°)\u003c\/li\u003e\n\u003cli\u003e“3D model will be provided” (listed alongside the camera and angle adjustable bracket)\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eApplications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e3D reconstruction and environment modeling (indoor)\u003c\/li\u003e\n\u003cli\u003e3D visual mapping, navigation and surveying (as listed)\u003c\/li\u003e\n\u003cli\u003eClose-range measurement (blind area as low as 0.25 m)\u003c\/li\u003e\n\u003cli\u003eObject recognition, target detection, and tracking workflows (as listed in course topics)\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eTutorials\u003c\/h2\u003e\u003cp\u003eTutorial link (official study page): \u003ca href=\"http:\/\/www.yahboom.net\/study\/AIVIEW_Camera\" rel=\"noopener\" target=\"_blank\"\u003ehttp:\/\/www.yahboom.net\/study\/AIVIEW_Camera\u003c\/a\u003e\u003c\/p\u003e\u003ch3\u003eDepth camera usage course (topics listed)\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eCamera usage instructions \/ Linux basics (listed)\u003c\/strong\u003e: Introduction to Linux system; Ubuntu file system; Ubuntu common commands; Ubuntu common editors; Ubuntu software operation commands; virtual machine installation; SSH remote control; VNC remote control; transfer files remotely; driver library and communication; static IP and hotspot mode; bind device ID; capacity expansion and resource; update system software sources; set root user password; sudo free password; connect to WiFi network; view system version; customized service management; back up system image\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOpenCV course (listed)\u003c\/strong\u003e: Opencv Source CV Introduction; image reading and display; picture writing; picture quality; pixel operation; picture scaling; picture cutting; picture translation; picture mirroring; affine transformation; picture rotation; perspective transformation; grayscale processing; image binarization; edge detection; line segment drawing; rectangle and circle drawing; text and picture drawing\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS1 basic course (listed)\u003c\/strong\u003e: ROS introduction; ROS installation; ROS common command tools; ROS workspace; ROS function package; ROS node; ROS topic publisher; ROS topic subscribers; ROS service client; ROS service server; ROS action client; ROS action server; ROS custom message reception; ROS-launch file; ROS-TF transformation; ROS parameter service; ROS-rviz use; ROS-rqt tool usage; topic message recording and; urdf model introduction; gazebo introduction; ROS distributed communication\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS1 Mediapipe course (listed)\u003c\/strong\u003e: hand detection; posture detection; overall detection; face detection; face recognition; face effects; 3D object recognition; brush; finger control; gesture recognition\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS1 + OpenCV application (listed)\u003c\/strong\u003e: camera calibration; QR code\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAdditional ROS + OpenCV topics (listed)\u003c\/strong\u003e: 3. Human pose estimation; 4. Target Detection; 5. ROS+Opencv basics; 6. Face recognition; 7. harris corner detection; 8. Target tracking algorithm; 9. Contour moment; 10. Polygon outline; 11. Discrete fourier transform algorithm; 12. Edge detection algorithm; 13. Face detection algorithm; 14. Optical flow detection algorithm; 15. Contour detection; 16. General contour detection; 17. Feature point tracking; 18. HLS color filtering; 19. Hough circle detection; 20. Hough linear detection; 21. HSV color filtering; 22. LK optical flow algorithm; 23. Human detection algorithm; 24. Phase dependent displacement; 25. Image pyramid sampling algorithm; 26. RGB color filtering; 27. Clear background detection; 28. Simplified optical flow algorithm; 29. Simple filter; 30. Threshold image processing; 31. Watershed segmentation algorithm; 32. Data conversion and point cloud; 33. AR vision; 34. AR QR code; 35. Color recognition; 36. Object tracking\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS2 basic course (listed)\u003c\/strong\u003e: Introduction to ROS2; ROS2 install Humble; ROS2 development environment; ROS2 workspace; ROS2 function package; ROS2 node; ROS2 topic communication; ROS2 service communication; ROS2 action communication; ROS2 custom interface message; ROS2 parameter service case; ROS2 meta-function package; ROS2 distributed communication; ROS2 DDS; ROS2 time related API; ROS2 common command tools; ROS2 rviz2 use; ROS2 rqt toolbox; ROS2 Launch startup file; ROS2 recording and playback tool; ROS2 URDF model; ROS2 Gazebo simulation platform; ROS2 TF2 coordinate transformation\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS2 OpenCV courses (listed)\u003c\/strong\u003e: ROS+opencv application; QR code creation and recognition; AR vision\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS2 mediapipe course (listed)\u003c\/strong\u003e: hand detection; posture detection; overall detection; face detection; personal insurance identification\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eROS2 depth camera series courses (listed)\u003c\/strong\u003e: depth camera usage; camera internal parameter calibration; color tracking; KCF object tracking; ORB_SLAM2 basics; ORB_SLAM2 PCL mapping; ORB_SLAM2 Octomap mapping\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor pre-sales compatibility questions or post-sales support, contact support@rcdrone.top or visit https:\/\/rcdrone.top\/.\u003c\/p\u003e\u003ch2 id=\"details\"\u003eDetails\u003c\/h2\u003e\u003cdiv class=\"details-gallery\"\u003e\n\u003cimg alt=\"Yahboom AI VIEW binocular structured light 3D depth camera for ROS robots, front view\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS.jpg?v=1782298278\"\u003e\u003cp\u003eAI VIEW combines binocular stereo and structured light to deliver fast RGB‑D depth sensing for ROS robot projects.\u003c\/p\u003e\n\u003cimg alt=\"AI VIEW depth camera application icons: ROS1\/ROS2, Raspberry Pi, Jetson, PC, 3D measurement\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_59c39010-96e6-4ae0-812b-b01781d46fb1.jpg?v=1782298284\"\u003e\u003cp\u003eWorks across common robot platforms including Raspberry Pi, Jetson, and PC for mapping, measurement, and perception tasks.\u003c\/p\u003e\n\u003cimg alt=\"AI VIEW depth camera specification sheet with dimensions, ports, and performance table\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_e4fef4b0-2487-46e8-bbf9-441104185d2b.jpg?v=1782298290\"\u003e\u003cp\u003eDetailed mechanical drawings and core specs help with enclosure design and robot integration planning.\u003c\/p\u003e\n\u003cimg alt=\"Binocular structured light depth principle illustration comparing monocular vs binocular layout\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_97d772c0-786c-4cac-9b47-1938d383fef6.jpg?v=1782298296\"\u003e\u003cp\u003eBinocular structured light uses left\/right matching and triangulation to improve depth perception accuracy.\u003c\/p\u003e\n\u003cimg alt=\"Mini size comparison graphic for AI VIEW depth camera mounted on a small robot arm\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_c9bd6440-d31d-41d2-8b27-d6ce6b1f534a.jpg?v=1782298301\"\u003e\u003cp\u003eCompact form factor fits easily on robot arms and mobile platforms where space and weight matter.\u003c\/p\u003e\n\u003cimg alt=\"Depth field-of-view graphic for AI VIEW camera with 0.25–2.5 m range and wide angles\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_88421432-1ce5-4b3f-9491-9b67dc52bde3.jpg?v=1782298307\"\u003e\u003cp\u003eWide depth FOV supports close-range perception and broader scene capture for navigation and tracking.\u003c\/p\u003e\n\u003cimg alt=\"Close-range blind area graphic indicating minimum depth distance of 0.25 m for AI VIEW\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_ff44b058-0b4b-4369-8e6e-c43377e7b44d.jpg?v=1782298313\"\u003e\u003cp\u003eA short 0.25 m minimum range helps with near-field sensing such as end-effector positioning.\u003c\/p\u003e\n\u003cimg alt=\"Depth range 2.5 m example with point cloud \/ mapping visualization on a desktop interface\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_0f67aae1-0ee9-4c33-b204-5be488450a82.jpg?v=1782298319\"\u003e\u003cp\u003eDepth output can be used for 3D visual mapping workflows such as point clouds and environment reconstruction.\u003c\/p\u003e\n\u003cimg alt=\"Anti-glare capability graphic for AI VIEW depth camera with indoor use note\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_22505bbb-369f-4bff-bf1e-995984db8132.jpg?v=1782298325\"\u003e\u003cp\u003eDesigned to better resist strong light, with recommended use in indoor environments for best results.\u003c\/p\u003e\n\u003cimg alt=\"ROS1 and ROS2 support graphic with AI VIEW depth camera next to a laptop display\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_78dcf823-da94-4123-bc53-de50a3dedd60.jpg?v=1782298330\"\u003e\u003cp\u003eROS1 and ROS2 support helps streamline integration into existing robot software stacks.\u003c\/p\u003e\n\u003cimg alt=\"Orbbec SDK interface screenshot for RGBD camera configuration, streams, and point cloud tools\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_f2af929f-6a68-4c83-940c-d415768770ad.jpg?v=1782298337\"\u003e\u003cp\u003eSDK tools provide device configuration, stream capture, and point cloud data access for development.\u003c\/p\u003e\n\u003cimg alt=\"Angle-adjustable bracket accessory mounting the AI VIEW depth camera on a wheeled robot chassis\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_45bfdca0-c855-4d06-922b-22db1220e2a7.jpg?v=1782298343\"\u003e\u003cp\u003eAn optional adjustable bracket allows flexible mounting angles during robot prototyping and testing.\u003c\/p\u003e\n\u003cimg alt=\"Second specifications sheet for AI VIEW binocular depth camera with dimension drawings and table\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_12c75cda-b04f-42ca-8cbc-ff0c4111abf2.jpg?v=1782298349\"\u003e\u003cimg alt=\"Package contents graphic listing AI VIEW depth camera and angle-adjustable mounting bracket\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_16bd4a64-3628-4dd2-aca8-d262b04c8bab.jpg?v=1782298354\"\u003e\u003cp\u003eAvailable as the camera alone or bundled with an angle-adjustable bracket for easier installation.\u003c\/p\u003e\n\u003cimg alt=\"Depth camera usage course overview chart for AI VIEW tutorials and learning path\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_d2fec09c-7315-45a6-82da-d314d4ce6e19.jpg?v=1782298360\"\u003e\u003cp\u003eStep-by-step course materials cover common RGB‑D topics from basic setup to advanced functions.\u003c\/p\u003e\n\u003cimg alt=\"Tutorial link page layout for AI VIEW camera with ROS1 and ROS2 folders and example cases\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_6115fc7b-65cc-4373-806b-934419a4d75b.jpg?v=1782298366\"\u003e\u003cimg alt=\"ROS2 basic course and Raspberry Pi Docker course folder list for AI VIEW camera tutorials\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_a3b07dcf-920f-432c-b29c-912bb8b090b6.jpg?v=1782298373\"\u003e\u003cimg alt=\"Case experience grid: hand detection, ORB-SLAM2 mapping, ARTags, OpenCV, depth map, color tracking\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_60873989-08f6-43a3-8fec-ac00af4015a1.jpg?v=1782298379\"\u003e\u003cp\u003eExample projects include SLAM mapping, AR tags, OpenCV processing, and depth-map applications for learning.\u003c\/p\u003e\n\u003cimg alt=\"Compatibility graphic for Yahboom AI VIEW RGBD 3D depth camera showing support for Raspberry Pi, Jetson, and ROS robots\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_26eda721-41c0-4d96-a81f-9692304431ff.jpg?v=1782298385\"\u003e\u003cp\u003eThe AI VIEW binocular structured-light RGBD depth camera is presented as compatible with Raspberry Pi, NVIDIA Jetson, and ROS1\/ROS2 robot platforms.\u003c\/p\u003e\n\u003cimg alt=\"Compatibility graphic for Yahboom AI VIEW 3D depth camera SDK with ROS1\/ROS2, C\/C++, Java, Python, Windows, Linux, Android, Unity\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_ccc6d964-8071-4636-8b00-137593cb4661.jpg?v=1782298390\"\u003e\u003cp\u003eThe SDK includes wrappers for ROS1\/ROS2 and common languages and platforms like C\/C++, Java, Python, Windows, Linux, Android, and Unity.\u003c\/p\u003e\n\u003cimg alt=\"Yahboom AI VIEW binocular structured light 3D depth camera with dual lenses and USB-C port on black housing\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_2807645f-f88c-44cf-93fa-688861d7f21d.jpg?v=1782298396\"\u003e\u003cp\u003eThe Yahboom AI VIEW structured light RGB-D camera features a compact black enclosure with dual front lenses and a USB-C connection for PC or robot setups.\u003c\/p\u003e\n\u003cimg alt=\"Yahboom AI VIEW binocular structured-light 3D depth camera with USB-C cable, mounting bracket, and screws\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_bed25575-5e46-475a-bcae-4efeccde3c25.jpg?v=1782298402\"\u003e\u003cp\u003eThe Yahboom AI VIEW depth camera kit includes a USB‑C cable plus a mounting bracket and hardware for easier robot integration.\u003c\/p\u003e\n\u003cimg alt=\"Dimensioned mounting bracket drawing in mm for Yahboom AI VIEW depth camera, with adjustable angle bracket and base plate\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_99f458bc-a8fe-4356-87a3-baf18d384737.jpg?v=1782298407\"\u003e\u003cp\u003eThe adjustable-angle bracket and fixed base plate dimensions help plan mounting and hole spacing for a tidy robot install.\u003c\/p\u003e\n\u003cimg alt=\"Yahboom AI VIEW binocular structured light 3D depth camera module with dual lenses in black housing\" loading=\"lazy\" src=\"https:\/\/rcdrone.top\/cdn\/shop\/files\/AI-VIEW-Depth-Camera-with-Binocular-structured-light-for-ROS_5da1c5d0-9e68-4432-b954-9aafa7521419.jpg?v=1782298413\"\u003e\u003cp\u003eThe Yahboom AI VIEW RGB-D depth camera uses a compact binocular front layout that’s easy to mount on ROS robots.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Yahboom","offers":[{"title":"separate camera","offer_id":53135640199392,"sku":"6000400466-1","price":243.8,"currency_code":"USD","in_stock":true},{"title":"camera + 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