Files
UA-.NETStandard/samples/Robotics/BinPickingCell/README.md
Marc SchierandCopilot cef83550cb OPC UA Vision: a vision-guided bin-picking demo an LLM agent can see and drive (#4235)
# Description

Implements **OPC UA — Vision** and uses it to build the demo the
companion specifications were drafted for: an eye-in-hand camera watches
a bin of parts, a language model *looks at the frame*, decides which
part matches the instruction, and commands the robot through Robot
Intent — with the OpenUSD viewer showing the arm move and the bin empty
out.

> **Draft, and stacked.**
[#4195](https://github.com/OPCFoundation/UA-.NETStandard/pull/4195) has
merged and master is merged in, so what is left on top of `master` is
the Vision work plus the unmerged `marcschier/ai-model-management`
branch, which the demo needs for the model/dataset/deployment
provenance. Review the Vision commits; the AI Model Management work
lands with its own PR.

## What is here

**The specification, implemented.** `Opc.Ua.Vision` is generated from
the spec's own `Opc.Ua.Vision.NodeSet2.xml`, vendored byte-identically
(SHA-256 `79C592C6…`, verified against a fresh download and stored
LF-preserved like the Robot Intent NodeSet). `Opc.Ua.Vision.Server`
builds the §4.2 discovery object, sensors, the coordinate-frame tree,
calibrations, media endpoints, inference pipelines and the §9 feedback
methods, with rendering and inference behind injectable providers.
`Opc.Ua.Vision.Client` is built on the generated ObjectType proxies and
composes transforms across the frame tree, which is what turns a
detection in camera coordinates into a pose a robot can act on.

**Two perception paths behind one contract**, which is exactly what
`InferenceLocationEnum` is for. `OnServer` is a deterministic detector
derived from the stage's ground truth — no model, no network, no GPU, so
CI can exercise the whole loop. `EdgeOffServer` is the agent: it sees
the frame over MCP and calls `SubmitDetections`, and the Server
publishes results it did not compute. A client reads
`DetectionResultType` identically either way.

**The agent's eyes.** `tools/Opc.Ua.Mcp.Vision` adds 22 `vision_*`
tools, which with the four shared connection tools makes the `vision`
profile 26; `vision_get_frame` returns the camera image as an MCP
`ImageContentBlock`, so the model looks at pixels rather than reading a
description of them. Tool profiles now compose — `--profile
vision,robotics` yields 62 tools — so one agent can both see and act
without dragging in the full 136-tool catalogue.

**The cell.** `samples/Robotics/BinPickingCell` follows the spec's own
Robotics-Vision Addendum: the `world → robot_base → flange →
gripper_tcp` frame tree with `camera_eih` on the flange, the `HandEye`
extrinsics and the `Intrinsics612x512` intrinsics — the addendum's
2448×2048 calibration scaled to the 4×4-binned grid the camera actually
delivers. `samples/Robotics/BinPickingClient` hosts the composed MCP
catalogue and optionally the viewer.

**Documentation.** `docs/Vision.md` (~800 lines) covers the model,
hosting, the build context, every topology builder, both perception
paths, feedback, the MCP profile and the limitations; linked from
`docs/README.md`, with the profile table in `docs/McpServer.md` and
READMEs for both samples.

## Evidence, not assertions

Each of these was measured on a running system rather than assumed:

| Claim | Evidence |
|---|---|
| The camera sees the bin | 612×512 frame with the bin and all five
parts in view — red `(212,47,47)`, green `(61,193,71)`, blue
`(54,85,218)`, yellow `(215,196,58)`, orange `(209,119,55)` |
| An agent can act on what it sees | Over MCP, `vision_get_frame`
returns a 612×512 PNG that decodes from base64 to 1,254,051 bytes, the
descriptor beside the detections says 612×512, and all five
`BoundingBox2D` centres land **inside** the frame on the pixel colour
their own detection claims |
| The geometry is right | A detection composed `camera_eih → world`
lands on the authored position, residual **0.0000 m** — on both the
on-server and off-server paths |
| The detector tracks the world | Placing a part drops the next scan
from 5 detections to 4, with that part absent |
| The robot obeys the agent | Scripted run took command authority and
completed a pick and a place, both `Succeeded` |
| Tool catalogues are honest | Counted from a running server: vision 26,
robotics 40, `vision,robotics` 62, full 136, **zero duplicates** |
| Every node is browsable by NodeId | Eight representative NodeIds —
both folders, a pipeline, a frame, the sensor, its Calibrations folder,
the HandEye calibration, the Media folder — all `Good` |

That tool-count check matters because the profile tests collapse names
into a `HashSet` and *cannot see* a duplicate registration — so the new
tests count registrations, not names.

## Things that were wrong, and are not now

Writing the tests found three defects of one kind — code that answered
instead of refusing. A zero-norm quaternion was silently rewritten to
identity, so a caller with an all-zero orientation got a confident wrong
grasp pose. `SubmitCorrection` rewrote a null `ResultId` to empty and
called the sink anyway. A bad `StageIdentifier` **killed the host
process** inside native `UsdStage.Open`, via an exception .NET cannot
catch. All three now refuse loudly and are pinned by tests.

**Nodes that existed but could not be reached.** The node manager
indexes the Vision root before configurators run, so everything the
fluent builder grafted on afterwards — both folders, the pipelines with
their Results and Feedback, the frames, the sensors with their optics,
calibrations and media endpoints — was never added to the index.
Browsing *forward from a parent* worked, because that walks
`NodeState.Children` in memory; browsing any of those nodes *by its own
NodeId* returned `BadNodeIdUnknown`, which is how an ordinary client and
the MCP discovery tools navigate. Registration is now deferred and
flushed after each configurator. The first fix covered only the DI path
and left the documented non-DI fallback broken in exactly the same way,
so `ConfigureVisionAsync` now exists and registers what it builds.

That defect survived a green suite because every test browsed children.
The new tests assert by NodeId, and were checked against the broken code
— with the flush removed, they fail.

**Every Method was uncallable.** The Server passed 426 unit tests while
not one of its Methods could be invoked over a real session —
`RunInference` returned `Bad_TooManyArguments`, and so did every other
Method that takes arguments, which is all of them but `StartContinuous`
and `Stop`. Three independent faults, each sufficient on its own: the
Method nodes were never created (they are Optional children, and the
dispatcher guards every attachment with a null check, so it silently
attached nothing); nothing declared the arguments, so the stack
concluded none were expected; and `MethodDeclarationId` pointed at a
synthesised NodeId rather than the NodeSet declaration a client calls
with, so the lookup missed the instance Method entirely. The builder now
creates the Methods, the `Results` folder and the `Feedback` object when
a provider or sink is configured, declares every signature, and names
the right declaration.

Unit tests could not have caught this: they invoke the handler delegates
directly and never go through `MethodState.Call`. It took an end-to-end
test over a real session. Relatedly, children created by the generated
`CreateOrReplace` helpers carry no `ReferenceTypeId`, so nothing could
reach them — fixed once in the build context rather than at the several
dozen call sites.
**And one where I was wrong.** Earlier in this branch I reversed my own
agents' decision and made `SubmitDetections` accept an empty detection
set, reasoning that "I looked and the bin is empty" is a correct
observation and refusing it forces a correct agent to invent a
detection. The reasoning is sound; it is also an argument *against* the
specification rather than an implementation of it. §9.5 is normative and
explicit — its StatusCode table lists `Bad_InvalidArgument` for
"`Detections` empty; or `SubmitCorrection` supplies both or neither
corrected array".

Worse, **none of §9.5's argument rules were enforced anywhere** — the
dispatcher forwarded every submission straight to the feedback sink, so
conformance depended on whichever sink a host installed. They are Server
obligations, so they now live in the dispatcher, ahead of the sink,
proven by strict mocks that would throw if the sink were consulted. The
usability problem is real and does not go away by conforming, so it is
raised where it can be fixed:
[opcua-drafts#70](https://github.com/marcschier/opcua-drafts/issues/70).

## Tracking the updated drafts

The Vision, Robot Intent and AI Model Management NodeSets on
`opcua-drafts` `main` have moved, partly because of feedback this branch
raised. All three are re-vendored byte-identically — verified by
comparing git blob hashes against the upstream files rather than by eye
— and the implementations follow.

**Two statements that were previously inexpressible now have a wire
representation.** `SubmitDetections` takes `SceneIsEmpty` and
`SubmitCorrection` takes `RetractAll`, so an agent can report "I
examined this frame and there is nothing in it" — the terminating
condition of the bin-picking task — and can retract a false positive by
correcting a result down to nothing. Both are checked in both
directions, because the flag is exactly what separates a deliberate
empty observation from a lost payload: an empty array without the flag
is refused, and the flag with an array attached is refused as two
contradictory claims about one frame. Implemented in the dispatcher, the
client, the MCP tools the agent drives, and the sample cell.

Also absorbed: `LampType` and `LightingMode` became enums (§66),
`ProfileName` became `DefaultProfileName` on the endpoint (distinct from
the `ProfileName` a caller passes to `GetStreamEndpoint`, which keeps
its name), AI `Invoke`/`InvokeAsync` gained `PayloadUri` under the same
exactly-one rule, and AI `ListModels` gained a `ContinuationPoint` —
because `MaxResults` alone puts everything past the bound permanently
out of reach.

**OpenUSD is on `0.9.0-alpha`**, verified on the running cell rather
than by restore alone: D3D12 backend, 612×512 frame, the bin and all
five parts in view and detected — the same result `0.8.0-alpha`
produced.

The one local workaround that survives is `VisionMethodArguments`, and
its reason has changed rather than gone away: the builder materialises
these Methods as Optional children through `CreateOrReplace`, which
constructs the state object directly and never runs the generated
factory that now carries the signatures. Checked rather than assumed —
removing the declarations fails five of the eight
`VisionMethodSurfaceTests`.

## Review feedback

Three threads, all addressed in `0fe2803a3`:

- **The AI Model Management work is now a library family, not a
sample.** `src/Opc.Ua.AI` (model), `.Inference` (`IInferenceBackend` and
backends), `.Server` (node manager) and `.Client` (discovery, reads,
calls, artefact transfer), in the same shape as the Robotics and Vision
families; the samples become `samples/AI/ModelManagementServer` and
`ModelManagementClient`. The client library needed real work rather than
relocation: its browsing surface was `private` inside the sample's
scenario runner, so moving the file alone would have produced a library
nobody could call.
- **No cloud-vendor SDK is referenced anywhere.** Inference goes through
`Microsoft.Extensions.AI` — an `IChatClient` is implemented by hosted
services and on-device runtimes alike, which is exactly the property
clause 8.1 asserts. `Azure.Identity` is gone: workload identity is not
an Azure feature, every platform projects a token into a file and each
SDK reads that file behind its own API, so the resolver reads it
directly. The comment claiming `Microsoft.Extensions.AI` would force a
`System.Text.Json` bump was stale — it pins 10.0.10, which this
repository already centralises on.
- **`BinPickingCell` and `BinPickingClient` moved into
`samples/Robotics/`**, which is where they belonged: the cell was
already linking the arm, its kinematics and both USD assets out of
`IntentEnabledRobot`.

## Upstream

Work that belonged elsewhere went elsewhere rather than being worked
around locally:

- **`openusd-dotnet`
[#13](https://github.com/marcschier/openusd-dotnet/pull/13)** — merged
and shipped in `0.8.0-alpha`. `SilkFrameCapture.Capture` rendered only
the first capture of a session and silently returned a blank frame for
every one after it. Also filed
[#14](https://github.com/marcschier/openusd-dotnet/issues/14) (no
camera-by-prim API) and
[#15](https://github.com/marcschier/openusd-dotnet/issues/15) (skipped
tests reported as passed — which fooled me for several runs). Both are
fixed; this branch takes `0.8.0-alpha` and deletes two workarounds,
including 143 lines of hand-rolled projection maths.
- **`opcua-drafts`
[#66](https://github.com/marcschier/opcua-drafts/issues/66)–[#69](https://github.com/marcschier/opcua-drafts/issues/69)**
— a close read of the spec produced 22 candidate ambiguities; 12 were
discarded as misreadings with clause citations and the remaining 10
filed. One is concrete: five members exist in the NodeId CSV that no
clause documents.
- **`opcua-drafts`
[#70](https://github.com/marcschier/opcua-drafts/issues/70)** — §9.5
could not express an empty observation or a false-positive retraction.
**Adopted**, with the explicit-flag resolution argued for:
`SubmitDetections` gained `SceneIsEmpty`, `SubmitCorrection` gained
`RetractAll`, and the corrected-array rule relaxed from *exactly one* to
*at most one*.
- **`opcua-drafts`
[#71](https://github.com/marcschier/opcua-drafts/issues/71)** — the
Vision NodeSet browse-named all 13 `InputArguments` / `OutputArguments`
Properties in the Vision namespace rather than the base namespace, so a
stack could not find them and every Method in the specification was
uncallable. **Fixed**; this branch now tracks the corrected artefact.

## The defect underneath it all

The end-to-end suite was removed earlier in this branch because nine of
its
fourteen tests failed on one symptom: a client could not open a
pipeline's
`Feedback` object or enumerate its `Results`, even though browsing the
same
parent listed both. Restoring it meant explaining that, and the
explanation
was not in Vision.

`RelativePathElement` initialised **`IsInverse` to `true`**. A caller
that
sets a `ReferenceTypeId` and a `TargetName` — which reads as *"the child
reached by this Reference"* — was therefore asking the Server for the
**inverse** Reference, and got `Bad_NoMatch` with nothing in the request
to
suggest why.

`ObjectTypeClient.ResolveChildNodeIdAsync` is such a caller, and it is
what
**every source-generated Optional-child accessor in the stack** is built
on
— the accessor whose own documentation cites
`AlarmConditionTypeClient.GetShelvingStateAsync`
as an example. Vision is merely where it surfaced, because Vision puts
two
Optional children on the path an off-Server agent must take. The sibling
helper in `StateMachineTypeClientExtensions` already set `IsInverse =
false`
by hand, which is the shape of a trap rather than a default.

The default is now forward, `ResolveChildNodeIdAsync` says so
explicitly,
and the existing test that had recorded `true` as *expected* now pins
`false` with the reasoning. Of the forty `RelativePathElement`
construction
sites in the tree, that accessor was **the only one relying on the
default at
all** — every deliberate caller already set it.

Two further defects were found underneath it, both real and both fixed:

- The generated `CreateOrReplace` helpers construct a child state object
directly and leave **`TypeDefinitionId`** unset as well as
`ReferenceTypeId`.
A child referenced by nothing cannot be browsed; one with no type
definition
is a malformed Object that a client filtering by type silently skips —
which
  is exactly what `EnumerateResultsAsync` does. Normalisation moved to
`VisionNodeManager`, so it also covers the case the builder cannot see:
a
result published **at runtime** by an inference provider, long after the
address space was built. That path produced results a client could list
but
  not read.
- `Opc.Ua.AI` shipped without an `AssemblyInfo`, so the solution built
with
  six `CA1014` warnings.

I had initially "fixed" this in the Vision client with Browse-based
fallbacks,
on the strength of a probe that appeared to show
`TranslateBrowsePathsToNodeIds`
failing even for `Server → ServerStatus`. That probe was wrong: it used
an
unqualified `ReferenceTypeIds`, which inside a `Opc.Ua.Vision.*`
namespace
binds to *Vision's* `ReferenceTypeIds` and yields a nonsense NodeId.
Chasing
that to the end is what turned up the real cause. **The fallbacks are
gone** —
they would have hidden a stack-wide bug behind a Vision-shaped
workaround, and
one of them matched on browse name while ignoring the namespace index.

`tests/Opc.Ua.Vision.Intent.Tests` is restored and back in `UA.slnx`,
passing
**14/14** on its own merit rather than through a client-side workaround.
A
registration test now pins the pipeline's `Feedback` and `Results`
children,
which nothing covered before.

## Running it, and what that found

The demo's premise is that a language model **looks at the bin and
reasons
about what it sees**. Running it end to end showed it could not, for
reasons
no test covered, because every one of them lived between components.

**The sample did not compile.** Two `CS8604` nullable errors with
`TreatWarningsAsErrors`, so neither the cell server nor the demo could
be
started at all. Worth recording that my first explanation was wrong: CI
*does*
build this project - the Linux leg's `net10.0` pass compiles it,
log-confirmed -
so this is not a coverage gap in the workflow, and no workflow change
was made.

**`Pick` and `Place` never moved the arm.** They were a delay plus a
gripper
action, so the operations reported `Succeeded` while nothing travelled.
They now
solve IK once and interpolate in joint space. **And the parts never
moved**: the
arm swung but the bin stayed full, because nothing tied the held object
to the
world state. The connector now creates 11 monitored items where it
created 6,
and a scripted run delivers `SeqNo=151` across 10 messages where it
delivered
`SeqNo=3` across 1.

**The frame was smuggled through a string field.** The media provider
put a
base64 *data URI* of the PNG into `VisionImageReferenceDataType.Uri` - a
field
meant to be a *reference*, while the bytes were already returned in the
inline
`ByteString`. Every response therefore shipped the image twice, and a
1,311,400-byte PNG became a 1,748,536-character string against a
`MaxStringLength` of 65,535: **26.7x over**. That is why raising
`MaxByteStringLength`, `MaxArrayLength` and `MaxMessageSize` never
helped - none
of them govern a `String`. Separately the MCP tool assigned raw bytes
where
`ImageContentBlock` requires base64, so the wire carried
`"data":"�PNG..."` -
every non-UTF-8 byte replaced by U+FFFD, destroying the image and
inflating the
response to 6.8 MB.

**The camera was aimed at nothing.** The arm's home pose, the flange
scan pose
the Vision model declared and the joint angles in the USD stage were
three
independent claims about where the camera was, and they disagreed - the
declared
flange orientation pointed the view 86 degrees away from the projection
camera.
Solving them as one thing exposed two further constraints that are easy
to miss:
the camera has to sit off the tool axis or it photographs its own
gripper, and
the IK branch has to be elbow-back or a link parks under the camera and
fills the
frame with the arm's own upper arm. A third was a regression this branch
introduced and `Opc.Ua.Robotics.Tests` caught - aiming a straight-down
camera
from a point on the base's own X-Z plane puts the wrist on the J4/J6
singularity, so every motion away from home fails to solve. A 15-degree
camera
roll, free because the camera still looks straight down, gets 25 degrees
clear,
which is the margin the poses before this branch had.

**The frame and the detections were different images.** The sensor
declared
2448x2048, the clip endpoint 1280x1024, and the renderer produced
640x512 - not
even the same aspect ratio. The ground-truth detector projects through
the
declared intrinsics, so its boxes lived in 2448x2048 space while an
agent was
handed a 640x512 picture: *"pick the red cube you can see"* arrived with
coordinates that pointed off the image. Everything now agrees at
612x512, an
exact 4x4 bin of the native sensor with the intrinsics scaled to match;
the
native size stays in the model and serial number, where it describes the
hardware rather than the image.

**`LatestClip` was created and never written**, so it reported
`Bad_NoDataAvailable` for the life of the Server and a consumer
following the
model - read the published frame, call the method only if there is none
- never
got a frame. The dispatcher now publishes a clip it has just encoded,
for every
Vision server rather than this sample alone.

One genuine API gap turned up on the way: `OpcUaServerOptions` exposes
`MaxByteStringLength`, `MaxArrayLength` and `MaxMessageSize` and **no
`MaxStringLength`**, so a Server that legitimately needs a long string
could not
raise the limit through the hosting API at all. Added, with tests. It is
not the
fix for anything above - that was a design bug - but the missing knob
was real.

## Not finished

- **Two projects sit below the repository's 80% line coverage.**
`Opc.Ua.Vision.OpenUsd` is at 71.1% — what is left only executes with a
real OpenUSD stage and plugin tree, which is not on every build agent.
`Opc.Ua.AI.Inference` is now at **86.7%**, up from 12.9%: the code this
branch *wrote* is covered by 25 tests, and `RestChatCompletionsBackend`
— previously the whole of the shortfall — is covered by 18 more against
a stubbed `HttpMessageHandler`, exercising success, refusal, throttling,
retry-after, timeout and cancellation without a network. Everything else
clears the bar — `Opc.Ua.Vision.Server` 92.1%, `Opc.Ua.AI` 91.4%,
`.Vision.Client` 88.1%, `Opc.Ua.Vision` 85.7%, `Opc.Ua.AI.Server` 80.1%,
all measured with coverlet. The CI coverage gate reports itself as
advisory and non-blocking.
- **`SamplesCollected` is not counted here, and `docs/Vision.md` now
says so.** Section 9.4 requires a Server to count a negative example
(`SceneIsEmpty` / `RetractAll` carrying a `GroundTruthLabel`) exactly as
it counts one carrying geometry. `VisionNodeManager` does not, and
structurally cannot: `SamplesCollected` is a property of
`LearningJobType`, which the *AI Model Management* companion defines,
and Vision reaches the job through a `NodeId` value rather than a
Reference **precisely so this model takes no dependency on the model
that defines it**. What the Server does guarantee is that the negative
example survives the hop intact — both flags are carried verbatim to
`IVisionFeedbackSink` — so a host that binds a learning job has
everything it needs to satisfy the clause on the counter it owns. Stated
in the limitations rather than left implied.

## Related Issues

Was stacked on #4195, now merged. No tracking issue yet for the Vision
implementation itself — happy to open one if you would like the design
recorded as an ADR before this goes further.

## Checklist

- [x] I have signed the
[CLA](https://opcfoundation.org/license/cla/ContributorLicenseAgreementv1.0.pdf)
and read the
[CONTRIBUTING](https://github.com/OPCFoundation/UA-.NETStandard/blob/master/CONTRIBUTING.md)
doc.
- [x] I have added tests that prove my fix is effective or that my
feature works and increased code coverage. — *Types 8562, Server 4072,
Client 2123, InformationModel 1063, Robotics 540, Tools 466, Vision 442,
AI 74 and the restored Vision+Intent end-to-end suite 14/14, all green
on net10.0. Only `.OpenUsd` (71.1%) is below the 80% bar — see Not
finished.*
- [x] I have added all necessary documentation.
- [x] I have verified that my changes do not introduce (new) build or
analyzer warnings. — *`dotnet build UA.slnx -c Release`: 0 errors, 0
warnings.*
- [x] I ran **all** tests locally using the **UA.slnx** solution against
at least .net **framework** and .net **10**, and all passed. — *net48:
Types 8555, Client 2126, Vision 385 green. Two net48 Server tests fail
(`CreateUserManagementSeamBindsTheModelToTheServerAsync`, and
`DurableDataValueQueueVerifyReferenceBatchingAsync` only under parallel
load); both were confirmed **pre-existing** by re-running them with the
`IsInverse` change reverted, which fails identically.*
- [ ] I fixed **all** failing and flaky tests in the CI pipelines and
**all** CodeQL warnings. — *The net48 build legs failed because the
restored end-to-end project used `ValueTask.FromResult` /
`string.Create`, which do not exist on .NET Framework; fixed in
`fb57522da` and verified building on every TFM.
`DisposeDrainsHeldConnectionCallbackBeforeListenerDisposal` failed once
on the Ubuntu Client leg — a 13 ms timing-sensitive reverse-connect
disposal test that passes locally 2123/2123 and touches no browse
paths.*
- [ ] I have addressed **all** PR feedback received.
## Typed Vision-guided Robotics MCP workflows

The branch now also makes the demo workflow first-class in the Full MCP
profile:

- replaces stringified Robotics intent and mission inputs with typed
request schemas and exact name-or-NodeId selectors;
- adds bounded operation/mission paging, stable step-to-operation
identity, retained mission discovery, and `robotics_wait_mission`;
- makes `vision_run_inference` return bounded typed detection,
inspection, or segmentation summaries in one call;
- adds same-session `robotics_vision_pick` to select a detection and
submit Pick or Pick/Place work without implicitly taking authority,
retrying, cancelling, or waiting; and
- starts Publish workers for classic subscriptions so an independently
launched OpenUSD viewer receives live robot and part updates.

The migration guide documents the intentionally breaking MCP
request-schema changes.

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 1dab1302-19c5-4a9b-a50c-d97d389713aa
Copilot-Session: a248a589-9a20-4372-868e-5d347e57001b
Copilot-Session: 99d1ab42-f83a-41ab-bf3e-85bf81fadace
Copilot-Session: bcbc8ac9-5abd-42a8-8bac-e10533790e2e
2026-08-29 19:34:15 +02:00

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<!--
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OPC Foundation MIT License 1.00
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# Bin Picking Cell
Reference server for the vision-guided bin-picking sample. Hosts a
branch-stable four-axis palletizer as a Robot Intent controller, a
Vision companion with an eye-in-hand camera parented to the flange, an
in-address-space OpenUSD scene, and the frame tree the Robotics-Vision
Addendum's example uses:
```text
world → robot_base → flange → gripper_tcp
↳ camera_eih
```
```mermaid
flowchart TD
World["world<br/>/World"] --> Base["robot_base<br/>/World/Robot/Palletizer/Base"]
Base --> Flange["flange<br/>/World/Robot/Palletizer/.../Flange"]
Flange --> Tcp["gripper_tcp<br/>/World/Robot/Palletizer/.../Flange/Gripper/Tcp"]
Flange --> Camera["camera_eih<br/>/World/Robot/Palletizer/.../Flange/Camera"]
```
Five parts (`RedCube`, `GreenCylinder`, `BlueSphere`, `YellowSlab`,
`OrangeBrick`) sit in a bin on the workbench; a fixture is placed next
to it. The sample's paired client at
[`samples/Robotics/BinPickingClient`](../BinPickingClient) runs the
perception-to-action loop against this server, either as a scripted
demo or under the control of an MCP-connected language model.
The cell is the example that motivates the [Vision developer
guide](../../../docs/Vision.md) — every §5.12 convention (quaternion
`(x, y, z, w)`, metres, corner-datum principal point, empty-covariance
sentinel), every §6.4 media state and every facet the guide lists
appears in the cell's address space.
## Running
Prerequisites: .NET 10 SDK.
```powershell
dotnet run --project samples\Robotics\BinPickingCell\BinPickingCell.csproj -- --insecure
```
The server listens on `opc.tcp://localhost:62855/BinPickingCell` by
default. The endpoint URL and port are configurable through
`--host <name>` and `--port <number>`; the anonymous operator role is
mapped in code so the demo client can connect without user credentials.
`--insecure` is a demo convenience: it accepts any client certificate
and does not enforce trust. Do not use it in production.
## Inference-location option
The cell selects one perception path once at startup and pins it for
the lifetime of the process. The pipeline's advertised inference-
location facet is derived from this and cannot change afterwards, so
the cell always tells the truth about which path is in force.
- `--inferenceLocation OnServer` (default) — the deterministic
`BinPickingGroundTruthInferenceProvider` computes `DetectionResultType`
results locally. The pipeline advertises `VIS-Inference-OnServer`,
needs no GPU, no model and no network, and is what CI runs.
- `--inferenceLocation EdgeOffServer` — the pipeline exposes a
`VisionFeedbackType` bound to `BinPickingAgentInferenceProvider`; an
agent connected over MCP looks at the frame and calls
`SubmitDetections`. The pipeline advertises `VIS-Inference-OffServer`
and publishes results the Server itself did not compute. `RunInference`
and `StartContinuous` are refused with `Bad_NotSupported` — a client
requesting an on-Server compute path in this mode gets an actionable
refusal, not a silent stub.
The two paths are exclusive by construction: a pipeline binds either an
inference provider or a feedback sink, never both at once, because
mixing them would let a computed and a submitted result publish on the
same pipeline out of any known order.
## Startup options
| Option | Meaning |
|---|---|
| `--host <name>` | Endpoint host name. Default `localhost`. |
| `--port <number>` | Endpoint port. Default `62855`. |
| `--inferenceLocation OnServer\|EdgeOffServer` | Selects the perception path. `OnServer` is the default. |
| `--captureOnStartup true\|false` | Whether the capture-proof hosted service captures a still on startup and writes it to disk (see below). Default `true`. |
| `--artifactDirectory <path>` | Where the capture-proof hosted service writes its still. Defaults to a temp path chosen by the host. |
| `--insecure` | Demo-only, per the note above. |
The parser accepts `OnServer`, `EdgeOffServer`, `OffServer`,
`on-server`, `off-server` and their case-insensitive variants for
`--inferenceLocation`. Unknown values silently fall back to `OnServer`
rather than failing to start.
## What the cell publishes
- Under `Server/RobotIntent`, one Robot Intent controller
(`BinPickingController`) with four axes (`J1` base yaw, `J2` shoulder,
`J3` elbow and `J4` tool roll), lookup tables for `Bin`, `Fixture`,
one home location per part and `ParallelGripper`. The controller
ships `Pick` and `Place` intents targeting the sample parts.
- Under `Server/Vision`:
- The frame tree above. Every frame carries a unit `(x, y, z, w)`
quaternion and a metres-based position; `camera_eih` is authored
with the `EyeInHand` hand-eye pose the addendum specifies.
- `BinPickingCameraTwin`, an `ImageSensorType` with
`RealityKind = Simulated`, `Modality = Area2D`, an
`IntrinsicCalibrationType` (Zhang method, residual 0.21 pixels), a
`HandEye` `ExtrinsicCalibrationType` (`EyeInHand` mount, residual
0.0008), an `IVisionSimulatedType` interface pointing at the USD
stage and `Camera` prim, a live RTSP `StreamEndpointType` and a
`PickFrames` `ClipEndpointType` with inline delivery enabled up to
32 MiB.
- `BinPickingPipeline` (`InferencePipelineType`) bound to the sensor
twin, with the deployment reference `OnServerDeployment` and either
the ground-truth inference provider or the agent inference provider
depending on `--inferenceLocation`.
- Under `Server/OpenUSD`, the composed `Cell.usda` stage the sensor
renders from.
- Under `Server/WorldState`, one position variable per part, in the world
frame. This is the cell's **simulation ground truth**, not a standard OPC
UA concept: a part lying in a bin is not something Robot Intent or Vision
models, and the scene has to be drivable from the address space to be
watchable. The OpenUSD live bindings follow these variables, so a picked
part moves in the viewport, and a client comparing what the detector
claims against where the part actually is has both halves.
## The USD stage
The scene is authored in `Assets/Cell.usda` and is extracted at
startup by `BinPickingCellStage.Extract()` into a working directory the
`BinPickingMediaProvider` and `OpenUsdSceneCameraCaptureProvider` share.
It references the cell-specific `palletizer-arm.usda` and
`palletizer-gripper.usda` assets, plus the shared gripper geometry, adds
the bin, fixture and parts, and parents the eye-in-hand `UsdGeomCamera`
to the flange so the view moves with the arm.
### Scene lighting is load-bearing
The stage is lit by a single `DomeLight` at intensity 1000.
**Do not reintroduce a `DistantLight`** — at any intensity that shows
geometry, a `DistantLight` blows every surface to pure white regardless
of material, and the point of this cell is that a vision-language model
can pick "the red cube" by looking at the frame. Under a `DomeLight`
the five parts measure `red (220, 37, 37)`, `green (37, 208, 49)`,
`blue (37, 73, 233)` — distinct enough for an LLM to reason about.
The `Cell.usda` header records this contract explicitly so a future
scene-authoring change does not silently break the perception path.
### Frame tree contract
- `/World` is the `world` frame origin.
- `/World/Robot/Palletizer/Base` is the `robot_base` frame.
- `/World/Robot/Palletizer/Base/J1/J2/J3/Leveling/J4/Flange` is the
`flange` (mechanical interface).
- `/World/Robot/Palletizer/.../Flange/Camera` is the `camera_eih`
`UsdGeomCamera` the Vision sensor renders from.
- `/World/Robot/Palletizer/.../Flange/Gripper/Tcp` is `gripper_tcp`.
The vision-side `flange` frame is authored at the scan pose the arm
would hold to point the eye-in-hand camera at the bin. In a live cell
the flange frame is dynamic and reflects the current joint state; for
this static-sample demo it is pinned to the scan pose so a consumer
composing `camera_eih → flange → robot_base → world` lands on the parts'
authored world positions — which is exactly what the ground-truth
detector reports for each detection's `Pose`. This is why the vision-
side frame ids match the robot-side frame ids exactly: the client can
compose a detection's pose from the camera into the world frame using
`VisionFrameGraph` and get a value it can hand straight to the robot-
side `Pick` intent.
The scan pose is one analytic palletizer configuration: TCP
`(0.60, 0, 0.32)` and flange `(0.60, 0, 0.505)` in `robot_base`.
The camera is 20 mm along flange `+X` and 160 mm along flange `+Z`,
which composes to world position `(0.60, -0.16, 1.405)`. The extra
180-degree camera convention transform accounts for USD cameras
looking down local `-Z` while Vision projection uses camera-forward
`+Z`.
The visual and numeric chain use the same geometry:
- shoulder height 0.280 m;
- upper arm and forearm 0.480 m each;
- flange-to-jaw-centre TCP 0.185 m along flange `+X`;
- mechanical leveling `90° - J2 - J3`, so the tool remains vertical;
- `J4` rolls around the down-facing tool axis, keeping jaw aperture
visible without introducing offset-wrist IK branches.
The analytic IK emits at most the two real elbow branches, rejects
unsupported pitch or roll, and chooses the nearest collision-clear
branch. It does not generate periodic duplicates or run a numerical
seed search, so a Cartesian leg cannot silently switch to an identical-
looking but discontinuous wrist configuration.
### Detected-pose picking and collision
`Pick` targets the selected detection pose, not the containing
Location's centre. The target provider stores result id, timestamp,
source frame and world pose by class label. Off-server detections must
use the calibrated `camera_eih` frame and remain within 80 mm of the
simulated part; targets expire after ten seconds. Only the built-in
on-server ground-truth path may fall back to current simulation state.
Motion retracts vertically, crosses at a clear height, descends, closes
or opens the jaws, and reverses the exact local approach before the
operation completes. A following Pick at the same fixture XY skips the
cross-cell traverse. The collision model uses per-link radii and tests
the bench, bin walls, fixture plate and pegs, every non-target part, the
accumulated stack, and an explicit box swept by the held part.
## What an agent actually receives
`vision_get_frame` (MCP) and `GetClip` (OPC UA) return a **612 × 512
PNG**, delivered as inline bytes in the method's `ByteString` output and
base64-encoded into the MCP `ImageContentBlock`. The
`VisionImageReferenceDataType` alongside it carries a
`opcua-inline://…` **reference** and the frame's dimensions — it does not
carry the image, which would ship the payload twice.
612 × 512 is what the sensor declares, what the clip endpoint declares,
what the intrinsics describe and what the renderer produces. The
simulated device is a 2448 × 2048 area-scan camera operated with 4 × 4
binning, so the calibrated intrinsics are divided by four and the
Brown-Conrady coefficients — expressed in normalised image coordinates —
carry over unchanged. The native size survives only in the model and
serial number, where it identifies the hardware rather than the image.
This matters because the ground-truth detector projects through the
declared intrinsics: the `BoundingBox2D` on every detection is in the
same pixel frame as the PNG an agent was handed. Previously the sensor
said 2448 × 2048, the clip endpoint said 1280 × 1024 and the renderer
produced 640 × 512 — not even the same aspect ratio — so a model asked
to "pick the red cube you can see" got a picture and a set of
coordinates that pointed off it.
After a successful `GetClip`, the Server publishes the frame on the clip
endpoint's `LatestClip` and its descriptor on `LatestClipMetadata`, so a
consumer that follows the model — read the published frame, call the
method only if there is none — gets a frame rather than a permanent
`Bad_NoDataAvailable`.
## Rendering behaviour on CI
The `Opc.Ua.Vision.OpenUsd` capture provider needs a native OpenUSD
renderer payload plus a usable graphics device to produce pixels. On CI
neither is present — the provider reports
`SceneCameraCaptureBackend.NoRenderingBackend` on `UnavailableReason`,
and every `LatestClip` read against `PickFrames` reports
`Bad_NoDataAvailable`. The sensor still exists in the address space,
every browse still works, every calibration is still readable and the
inference proof hosted service still updates the world state.
This is by design: the point of the CI leg is to exercise the address
space, the fluent builder, the provider abstractions and the client
plumbing, not to prove that the machine has a GPU. `--demo` on the
paired client skips its "compose frame → world" step gracefully when
the frame is unavailable rather than falsely reporting a rendering
failure.
On a workstation with the renderer payload installed and a usable
graphics device, the same sensor renders normally and returns encoded
PNG bytes through the inline `LatestClip` or the by-reference
`GetClip` path.
## Ground-truth vs agent inference
- **Ground-truth path** (`--inferenceLocation OnServer`):
`BinPickingGroundTruthInferenceProvider` reads the current world
state from `BinPickingWorldState`, projects each part into the
camera through the authored `HandEye` transform and intrinsics, and
publishes a `DetectionResultType` with the corresponding class label,
bounding box and pose. Because this reads real geometry, the poses
it publishes are the ones a correct agent would submit — which is
what makes the ground-truth path useful as a check on an agent's
answer.
- **Agent path** (`--inferenceLocation EdgeOffServer`):
`BinPickingAgentInferenceProvider` is the sample's off-Server
feedback sink. `SubmitDetections`, `SubmitCorrection` and
`SubmitImageReference` are accepted; `RunInference`,
`StartContinuous`, `Stop` and `SubmitInspectionResult` are refused
with `Bad_NotSupported` because this pipeline exposes
`DetectionResultType` results only and has no on-Server compute
path. The agent's submissions are validated before they land — see
below.
Two hosted services publish loop-proof output regardless of MCP being
attached:
- `BinPickingCaptureProof` captures a still on startup (skipped with
`--captureOnStartup false`), writes it to
`--artifactDirectory` when set, and logs the resulting size or the
`NoRenderingBackend` reason. Useful for verifying the render path
from a CI leg.
- `BinPickingInferenceProof` (on-server) drives one round of the
deterministic detector and mutates `BinPickingWorldState`, or
`BinPickingOffServerProof` (off-server) drives one round of agent
submissions with valid detections. Both prove the end-to-end write
path independently of the MCP tool surface. The on-server proof
**restores the bin afterwards**: it runs before any client connects,
and leaving a part picked would mean the paired client's demo started
against a world it had not changed itself.
The robot moves the parts too. `Pick` travels to its `Source`, closes the
gripper around the current pose of the part named by the intent's
`ObjectClass`, marks it held only after the jaws finish closing, then
retracts. The part's world position follows the tool until `Place`
opens the gripper, settles it on the highest support, and retracts. The
ground-truth detector projects from those same positions, so it stops
reporting a part that has been moved out of the bin — which is what
makes the paired client's `--demo` verification real rather than a
formality.
## Feedback validation
When an agent submits detections through
`vision_submit_detections` (or `vision_submit_correction`), the sample's
feedback sink validates every field and refuses malformed submissions
with `Bad_InvalidArgument` and a message the agent can act on:
- **Unknown class label** — refused with the exact list of parts that
do exist: `Detection 0 class 'PurplePyramid' is not a part in this
cell. Known classes: RedCube, GreenCylinder, BlueSphere, YellowSlab,
OrangeBrick.`
- **Confidence outside `[0, 1]`** — refused with the observed value.
- **Bounding box outside the image** — refused with the box centre,
extents and the image dimensions.
- **Non-positive box extents** — refused with the extents.
- **`NaN` in a box or pose** — refused with the detection index.
- **Zero-norm quaternion or `Orientation` with fewer than four
components** — refused with an explanation that references §5.12.
- **`Position` with fewer than three components** — refused likewise.
- **Pose frame other than `camera_eih`** — refused with both the
submitted and calibrated frame ids.
- **Pose more than 80 mm from the matching simulated part** — refused
with the measured residual.
- **Purpose not in `Overlay | Reconciliation | GroundTruthLabel |
Trigger`** — refused with the offending value.
- **More than 15 detections in a single submission** — refused as
implausible for the five-part cell.
An **empty** detection set is refused too. §9.5 lists "`Detections`
empty" as `Bad_InvalidArgument`, and requires `SubmitCorrection` to
carry *exactly one* non-empty corrected array. The cell conforms, which
has a consequence worth knowing: an agent that has emptied the bin
cannot report "I looked and there is nothing there", and a false
positive cannot be retracted by correcting a result down to nothing.
Both are raised against the draft rather than worked around here — see
the [Vision developer guide](../../../docs/Vision.md#limitations).
`SubmitInspectionResult` is refused with `Bad_NotSupported` regardless
of the arguments: this pipeline is a detection pipeline, not an
inspection pipeline, and an agent submitting an inspection result is
confused about which pipeline this is.
## Related samples and docs
- [BinPickingClient](../BinPickingClient) — the paired client, with
`--demo` for the scripted loop and `--mcp` for an agent-driven one.
- [Vision developer guide](../../../docs/Vision.md) — the
companion documentation for `Opc.Ua.Vision*` and
`Opc.Ua.Mcp.Vision`.
- [Robotics developer guide](../../../docs/Robotics.md) — the sibling
companion; the Robot Intent controller in this cell is the topic of
that guide.
- [OpenUSD guide](../../../docs/OpenUsd.md) — the connector and scene
materialisation used to bind the address space to the USD stage.
- [MCP Server guide](../../../docs/McpServer.md) — profile composition
(`--profile vision,robotics`), tool tables and connection semantics.