Robotics and machine vision opticsPalo Alto, California

ROBOTICS / IMAGING / ILLUMINATION

Machine vision lens design services engineered as part of the robot.

Palo Alto Optics designs machine-vision optics, illumination, calibration, and optomechanical hardware for robotics, automation, and intelligent instruments. PAO is a fit when catalog components or bench setups cannot meet the real task, and can deliver architecture studies, custom lens models, lighting designs, integrated prototypes, calibration definitions, acceptance tests, and manufacturing-transfer documentation.

Discuss a robotics vision problem Review engineering scope

01Scene

02Illumination

03Imaging

04Calibration

05Robot decision

For 2D and 3D vision, line scan, inspection, guidance, and application-specific sensing.

01Engineering reality

Reliable vision begins with control of the photons and geometry.

An algorithm cannot recover information that the optical system never captured. Working distance, occlusion, motion, surface response, illumination, depth of field, calibration, and mechanical stability set the usable data quality.

Constrained viewpoints

Resolve field, access, occlusion, depth, resolution, and collision envelope around the task.

Uncontrolled surfaces and motion

Engineer illumination and exposure for glare, dark materials, texture, speed, vibration, and ambient light.

Calibration that survives

Tie camera, optics, lighting, mechanics, and robot coordinates to a maintainable calibration strategy.

02Project fit

Contact PAO when image quality, illumination, calibration, or packaging is limiting the machine decision.

The best fit is a robotics or inspection team that needs to define the vision architecture, exceed catalog-lens limits, stabilize calibration, or turn a promising bench setup into repeatable integrated hardware.

The task is defined but the optics are not

You know the feature, pose, defect, or robot decision, but working distance, field, sensor, lens, and lighting still need to be closed together.

The algorithm lacks reliable input

Glare, dark surfaces, motion, occlusion, depth, ambient light, or focus variation is reducing usable image information.

A bench setup must survive production

Camera, illumination, mounts, calibration, protection, service, and acceptance testing need a controlled product architecture.

ENGINEERING DECISION TABLE

Inputs that change the architecture, acceptance method, and program risk.

Input condition	Key metric	Design choice	Risk if unresolved
Target feature and machine decision	Pixels on feature, contrast, confidence, false calls	Sensor format, magnification, lens class, illumination geometry	The vision stack never receives separable information.
Field, depth, and working distance	Resolution across field and depth of field	Conventional, telecentric, multi-camera, or custom optics	Focus, perspective, or occlusion fails on real parts.
Surface, motion, and ambient light	Signal-to-background, exposure margin, blur	Bright-field, dark-field, diffuse, strobed, spectral lighting	Performance changes by finish, speed, or facility lighting.
Robot and service interfaces	Calibration repeatability and line-of-sight stability	Datums, rigid mounts, targets, recalibration triggers	Accuracy drifts after tool changes, impacts, or maintenance.

SELECTED ENGINEERING EVIDENCE

Published scope, verification method, and disclosure boundary.

These records describe documented engineering experience or the evidence plan PAO uses for new work. They do not imply that prior-employer programs were PAO customer engagements.

Integrated inspection-system experience

Scope: Documented prior-role work covering custom imaging, optomechanical packaging, tolerancing, supplier communication, metrology, and assembled-system test.
Verification: Representative image tests, dimensional or optical acceptance limits, calibration state, and model-to-test comparison.
Boundary: Named customers, exact system performance, quantities, and confidential implementation details are withheld.

Review documented systems experience

Task-based acceptance for new PAO work

Scope: Scene set, feature or defect definition, optical and illumination configuration, calibration state, operating conditions, and decision metric.
Verification: Tests use representative surfaces, poses, motion, ambient conditions, and defined pass/fail criteria rather than lens MTF alone.
Boundary: A feasibility review is required before committing detection, accuracy, cycle-time, or environmental performance.

Read the specification guide

03Engineering scope

From task geometry to calibrated vision hardware.

The architecture is driven by the decision the machine must make, the environment, and the evidence needed to verify performance.

Define a technical work package

Task and image-quality budget

Object features, defect size, pose, speed, field, working distance, depth, contrast, and confidence targets.

Imaging architecture

Area scan, line scan, stereo, structured light, telecentric, spectral, or custom lens and sensor selection.

Illumination design

Bright-field, dark-field, coaxial, diffuse, strobed, structured, multispectral, or task-specific lighting.

Optomechanical integration

Rigid camera-to-tool interfaces, protection, thermal behavior, focus retention, cable paths, and service access.

Calibration and correction

Intrinsic, extrinsic, distortion, flat-field, color or spectral, robot-frame, and field calibration.

Prototype and production

Test scenes, fixtures, acceptance metrics, supplier specifications, build support, and transfer.

04Technical envelope

Purpose-built optics for machine decisions.

Representative capability is shown with the context needed to qualify it. Program requirements control the final architecture and acceptance values.

Robot guidance

Imaging and illumination for localization, pick-and-place, insertion, manipulation, and tool alignment.

Industrial inspection

Defect, dimension, presence, surface, print, assembly, and process verification.

3D and depth sensing

Stereo, structured-light, time-of-flight support optics, projection, receiving, and calibration.

Large-format and line scan

High-resolution imaging for webs, panels, substrates, displays, and continuous inspection.

REFERENCE ENVELOPE

Imaging modes2D / 3D / line scanArchitecture selected from task and motion

Spectral optionsUV to SWIRSensor, material response, safety, and illumination dependent

Lens classesConventional to telecentricIncluding custom large-format and application-specific optics

CalibrationLens to robot frameIntrinsic, extrinsic, illumination, and geometric correction as required

Machine-vision performance is application specific. PAO defines measurable optical and calibration criteria against representative parts, surfaces, motion, environments, and decision thresholds.

05What you receive

Engineering outputs your team can review, build, test, and maintain.

The exact package follows the program stage and scope. Assumptions, interfaces, decisions, and acceptance evidence remain visible.

Vision architecture

Task geometry, optical path, sensor and lens selection, illumination concept, and performance budget.

Imaging design

Lens or relay models, MTF, distortion, depth of field, spectral behavior, and tolerances.

Illumination package

Geometry, source, optics, drive assumptions, thermal inputs, exposure, and ambient-light controls.

Calibration definition

Targets, fixtures, coordinate transforms, corrections, field procedure, and recalibration triggers.

Integrated optomechanics

Camera and lighting mounts, datums, protection, adjustment, service, and robot interfaces.

Acceptance plan

Representative scenes, metrics, operating conditions, test sequence, and release criteria.

06Controlled delivery

A local engineering interface from first review through release.

PAO leads the technical work, coordinates specialized fabrication and production resources under the project quality process, and keeps responsibility for requirements, interfaces, evidence, and issue closure clear.

01
Technical intake
Define the system boundary, decision to be made, current evidence, constraints, and confidentiality path.
02
Requirements and risk
Create measurable requirements, interface assumptions, performance budgets, and a ranked technical risk register.
03
Architecture and proof
Compare viable concepts and retire the highest-risk assumptions with analysis, breadboards, or targeted tests.
04
Detailed engineering
Develop controlled optical, mechanical, calibration, test, and supplier-ready documentation.
05
Build and verification
Support procurement, assembly, alignment, test correlation, root cause, and evidence-based iteration.
06
Release and transfer
Close acceptance criteria, configuration, supplier questions, manufacturing issues, and production handoff.

07Qualification questions

Questions engineering teams ask before engaging.

01Can PAO work with our existing camera and vision software?

Yes. PAO can define or redesign the optical, illumination, calibration, and mechanical layers around selected sensors and software interfaces.

02When is a custom lens justified?

A custom lens is justified when catalog optics cannot close field, package, distortion, depth, spectral, telecentricity, environmental, or production requirements with acceptable margin.

03How do you specify vision-system performance?

Requirements are tied to the machine task using representative features, surfaces, poses, working distances, motion, ambient conditions, calibration state, and decision metrics rather than relying only on lens MTF.

04What drives the cost and schedule of a robotics vision project?

The primary drivers are whether catalog optics can be used, the need for custom illumination or lenses, working-distance and package constraints, calibration complexity, environmental protection, prototype quantity, and the availability of representative parts and failure images.

05Can PAO take over an existing machine-vision design?

Yes. PAO can review the current camera, lens, lighting, CAD, calibration, images, and failure cases, then isolate whether the dominant limitation is optical, mechanical, environmental, calibration-related, or software-facing.

06Can you build and test the prototype?

Yes. The work package can include custom component sourcing, integrated optomechanics, assembly, alignment, calibration fixtures, representative-scene testing, acceptance evidence, and transfer documentation.

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