Parts that arrive in random orientations. Bins of mixed parts. Conveyors with parts that don't index. 2D and 3D vision guides the robot to the right part, in the right orientation, at the right pick angle — at line speed and without fixturing.
Fixturing adds tooling cost, changeover time, and a constraint on every new product. Vision-guided picking eliminates fixturing — the robot picks whatever the camera tells it is there, in whatever orientation. New products onboard in days, not months.
Most existing robot cells use mechanical fixtures or bowl feeders to present parts in known positions. We add a 2D vision station upstream of the robot; the camera sends per-part position and orientation to the robot controller. Fixtures stay (as fallback / overflow) but most picks become vision-guided.
Skip the fixture cost entirely. Spec a 2D vision station for flat-presented parts; spec a 3D structured-light station for bin-picking. The robot's pick path is computed from the camera data — no part presentation engineering required.
Camera (2D or 3D) captures the parts in the workspace.
AI identifies each part: type, orientation, pick-feasibility, occlusion.
Best pick selected; pick path computed; collision check against environment.
Robot pose + pick command sent to controller. Robot picks; verifies; places.
Tell us your line, your existing equipment, and your tolerance window. We'll come back with a retrofit assessment, a greenfield specification, and a rough cost estimate within two business days.