Editor’s pick
Machine Vision 3D Camera: Build a Depth-and-Vision Evidence Plan
A practical evaluation plan for deciding where compact dToF depth fits alongside RGB or stereo in a machine-vision application.
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Drone LiDAR Blog for UAV Engineering Teams
Practical Drone LiDAR guides for obstacle avoidance, solid-state dToF module selection, integration, point-cloud data and UAV engineering evaluation.
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Choose the engineering question behind your next decision.
Obstacle Avoidance
Drone Obstacle Avoidance
Sensing, coverage, sunlight, brake-margin and system-validation guides for UAV teams.
22 guides › Selection & Buying LiDAR Selection & BuyingSelection criteria, pricing questions and comparison content for B2B buyers.
36 guides › Applications LiDAR ApplicationsDrone obstacle avoidance, robotics mapping, industrial inspection and embedded vision.
26 guides › Data & Point Cloud Data & Point CloudDepth data, point cloud visualization, sample datasets and evaluation workflows.
9 guides › Integration Integration & SDK TutorialsType-C evaluation, UART communication, embedded platforms and practical sensor integration workflows.
19 guides ›
Latest articles
Newest Drone LiDAR technical posts.
LiDAR Applications
AR VR Depth Module: An Occlusion-Confidence Test Plan for Interactive Prototypes
A practical AR/VR depth-module evaluation plan that separates capability, spatial representation, interaction-zone behavior, and fallback evidence before a prototype expands.
· 8 min read
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Integration & SDK
LiDAR SDK Windows Linux Android ARM: Build a Portability Evidence Pack Before Your Field Pilot
Build a repeatable evidence pack for LiDAR SDK Windows Linux Android ARM evaluation before an embedded or field-pilot handoff.
· 13 min read
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LiDAR Selection & Buying
940nm VCSEL Solid State LiDAR: A Buyer’s 7-Test Evidence Plan
A practical seven-test plan for evaluating a 940nm VCSEL solid state LiDAR module with optical, data-path, documentation, and pilot evidence.
· 11 min read
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Data & Point Cloud
Point Cloud Processing Tutorials: A dToF Depth-to-Cloud Evaluation Workflow
A practical, repeatable workflow for turning compact dToF depth output into an inspectable point cloud before labeling, model work, or an application pilot.
· 11 min read
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Integration & SDK
Robot Obstacle Avoidance dToF Sensor: Build a Near-Field Observation Contract
A practical guide to giving a robot obstacle avoidance dToF sensor a bounded near-field observation role, from frames and data handoff to replayable pilot evidence.
· 9 min read
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LiDAR Applications
AGV AMR Navigation LiDAR Module: Define the Sensor’s Job Before Your Warehouse Pilot
Define the role of an AGV/AMR LiDAR module before a warehouse pilot: local observation, data handoff, mapping, or localization—and the evidence each role needs.
· 11 min read
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Continue by engineering task
Move from research to product evaluation.
01Avoid obstacles
Connect sensing coverage, environment and host logic to a UAV validation plan.
Open sensing guide › 02Integrate the modulePrepare the host, interface and development resources needed for evaluation.
Open documentation › 03Validate depth dataRequest point-cloud and depth data matched to the intended application scene.
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