Automotive

Zivid 3D cameras use multi-acquisition HDR and Vision Engine reflection filtering to capture accurate point clouds from reflective surfaces, including polished sheet metal, chrome fittings, and coated body panels. This capability is validated in automotive production environments, covering small shiny fasteners, stamped sheet metal in metal bins, and semi-shiny tote components with varying orientation.

The most common failure modes reported by automotive teams replacing existing 3D camera systems are: overheating under 24/7 production loads, poor resolution on small or complex parts, and calibration drift between shifts due to temperature variation. Zivid cameras address all three — with IP65 ingress protection, active thermal management, and calibration stability tested across continuous industrial operation.

Yes. Zivid cameras output a full-resolution 2D color image and a complete 3D point cloud in a single acquisition. AI segmentation runs on the 2D image; pick-pose estimation uses the 3D data — no separate 2D camera, no 2D-to-3D calibration, no synchronisation delays.

Automotive integration teams consistently cite 2D-to-3D calibration as a source of project delays, eliminating it is a meaningful reduction in integration complexity.

Zivid cameras are used for gap and offset measurement on car body panels to sub-millimeter accuracy, painted surface defect detection at fine resolution, in-line inspection of die-cast parts, quality checks across numerous part variants on a shared production line, battery pack inspection, and connector quality inspection at automotive suppliers.