Sub-system
A camera gives a projection; a robot needs a position in space. Three-dimensional sensing recovers depth, which is what allows a robot to pick a part from a heap rather than from a fixture — the capability that removes the most expensive part of many automation projects.
In one sentence
Three-dimensional sensing produces depth information about a scene, using structured light projection, stereo camera pairs, laser profile triangulation or time-of-flight measurement, so a robot can locate objects in space.
Structured light projects a known pattern and infers depth from how the pattern deforms across the surface — accurate at short range and disturbed by ambient light and shiny surfaces. Stereo infers depth from the disparity between two views and needs texture to match on, so it is often paired with a projected pattern. Laser profiling sweeps a line across a moving part and builds a very accurate profile, which suits inspection on a conveyor.
Bin picking is the application that motivated most of this. A heap of identical parts in a container is trivial for a person and was, for a long time, out of reach for a robot: the sensing must find graspable instances among overlapping objects, the planner must reach one without colliding with the bin, and the gripper must succeed on a partially occluded surface.
Most industrial parts are machined metal — specular, sometimes dark, occasionally both. Specular surfaces reflect projected patterns away from the sensor or produce inter-reflections that read as false geometry. Handling them takes polarisation, multiple exposures or careful angle control, and it is why demonstrations on matte plastic mislead.
Finding a part is not picking it. The system must choose which instance is graspable, plan a path into a confined bin without collision, and recover when the grasp fails or disturbs the pile. Grasp planning and failure recovery, not depth accuracy, are usually what decide whether a bin-picking cell meets its cycle time.
High-accuracy methods take multiple exposures and time; fast methods are noisier. The right choice depends on whether the task is measurement or guidance — a robot needs only enough accuracy to grasp, while dimensional inspection needs the full precision and can afford the cycle time.
Technology dependencies are solved by engineering; supply dependencies are solved by building something, which takes years.
Structured light and time-of-flight sensing depend on emitters from the photonics supply chain.
Compound semiconductorsDepth data is only useful with a planner that turns it into a reachable, collision-free grasp.
End effectorsThe transform between camera and robot must be known precisely, and it drifts with thermal and mechanical change.
Sensors and encodersEvery depth method is still a camera looking at a lit scene, and ambient light or a specular surface defeats it before any algorithm runs.
Industrial imagingOther pages in this map that name 3D sensing as something they cannot do without.
What each company supplies at this step, and — where a public figure exists — its share of this specific market — with what that share measures, the period it covers and who published it. Some rows also show the company’s own reported revenue for the segment covering this step, which is a different thing: it says how much this business matters to that company, not how much of the market it holds. Not a ranking and not a recommendation.
Supplies three-dimensional vision and guidance systems for robotics.
Supplies laser profilers and three-dimensional measurement systems.
Supplies machine vision and robotics perception products.
Supplies metrology and three-dimensional measurement systems.
Supplies the emitters and photodetectors that structured-light and time-of-flight sensors are built around.
Supplies the laser arrays behind most depth-sensing modules, consumer and industrial alike.
Supplies structured-light scanners built for bin picking, where the scene moves and the parts overlap.
Supplies the depth-capable image sensors the modules are built on.
Whether learned grasping makes bin picking reliable enough for high-uptime production.
Whether depth sensing on specular metal surfaces becomes routine rather than an integration project.
Whether sensor cost falls enough to put three-dimensional guidance on ordinary cells.
Each page explains one technology in plain language, states what it depends on, and names companies by what they supply at that step. Company roles are described qualitatively and deliberately carry no market shares, revenue figures or rankings — those change faster than an explainer can, and a stale number is worse than none. Ticker links point at company pages on this site and are provided for reference only.
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