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Challenge

Build a Robot-Cell Mechanical Interference Disposition Engine

Evaluate dimensional metrology scan failures against MoveIt geometric collision envelopes. Synthesize disposition recommendations based on mechanical interference risks during automated assembly processes before scrapping expensive manufactured parts.

EngineeringHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Evaluate dimensional metrology scan failures against MoveIt geometric collision envelopes. Synthesize disposition recommendations based on mechanical interference risks during automated assembly processes before scrapping expensive manufactured parts.

Manufacturing Quality Engineer

Ingest non-conformance records containing dimensional laser scanner bounding box deviations.

Inject deviated dimensional measurements into MoveIt geometric shape definitions.

Perform collision checking simulations to detect physical interference during automated assembly insertion.

Assemble an audit-ready non-conformance dossier indicating collision risks for human engineering sign-off.

Multi-pane review console showing collision envelopes, defect images, and disposition draft.

Create simplified synthetic app records representing dimensional deviations and mating clearance measurements for robot assembly. Starter examples below are synthetic. They are not downloaded records.

MoveIt robotics Employs MoveIt geometric shape definitions and collision checking capabilities from Source 1 to evaluate interference.

dspy, pydantic, numpy. DSPy compiles optimized prompts and assertions to reliably categorize non-conformance dispositions based on simulated collision outputs. Local or hosted LLM capable of structured reasoning on numerical tolerance variances and boolean collision flags.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Correctly calculates interference risk percentage from measured dimensions and clearances.

Flags detected structural collisions as mandatory scrap dispositions.

Validates that disposition outputs follow strict engineering review board schemas.

```json [ { "input": { "part_serial": "CAST-BLK-891", "feature": "EXTERNAL_FLANGE", "nominal_mm": 50, "measured_mm": 51.5, "mating_clearance_mm": 2 }, "expected_output": { "part_serial": "CAST-BLK-891", "collision_detected": false, "disposition": "USE_AS_IS", "interference_risk_pct": 75, "engineering_signoff_required": true } }, { "input": { "part_serial": "CAST-BLK-892", "feature": "EXTERNAL_FLANGE", "nominal_mm": 50, "measured_mm": 52.5, "mating_clearance_mm": 2 }, "expected_output": { "part_serial": "CAST-BLK-892", "collision_detected": true, "disposition": "SCRAP", "interference_risk_pct": 100, "engineering_signoff_required": true } } ] ```

Read-only advisory disposition; does not scrap or accept physical parts without human engineer sign-off. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Read-only advisory disposition; does not scrap or accept physical parts without human engineer sign-off. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Correctly calculates interference risk percentage from measured dimensions and clearances. Flags detected structural collisions as mandatory scrap dispositions. Validates that disposition outputs follow strict engineering review board schemas.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Ingest non-conformance records containing dimensional laser scanner bounding box deviations. Inject deviated dimensional measurements into MoveIt geometric shape definitions. Perform collision checking simulations to detect physical interference during automated assembly insertion. Assemble an audit-ready non-conformance dossier indicating collision risks for human engineering sign-off.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Correctly calculates interference risk percentage from measured dimensions and clearances. Flags detected structural collisions as mandatory scrap dispositions. Validates that disposition outputs follow strict engineering review board schemas.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Multi-pane review console showing collision envelopes, defect images, and disposition draft.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Read-only advisory disposition; does not scrap or accept physical parts without human engineer sign-off.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Ingest non-conformance records containing dimensional laser scanner bounding box deviations.

  • Inject deviated dimensional measurements into MoveIt geometric shape definitions.

  • Perform collision checking simulations to detect physical interference during automated assembly insertion.

  • Assemble an audit-ready non-conformance dossier indicating collision risks for human engineering sign-off.

Resources and assets

Reference links and supporting material

Dataset notes

Create simplified synthetic app records representing dimensional deviations and mating clearance measurements for robot assembly. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

DSPy

Prompt and LM program optimization framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest non-conformance records containing dimensional laser scanner bounding box deviations. Inject deviate...
  • Correctly calculates interference risk percentage from measured dimensions and clearances. Flags detected s...
  • Multi-pane review console showing collision envelopes, defect images, and disposition draft.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 3 configured tools

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • DSPy · Optional
Training Infra
  • DSPy · Optional
Orchestration
  • DSPy · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Robot-Cell Mechanical Interference Disposition Engine