Skip to main content
Challenge

Build a Robot-Cell Weld Optical Inspection Defect Triage Planner

Parse automated optical inspection defect point clouds for preliminary geometric screening. Triage non-conforming weld assemblies, proposing simulated robot abrasive rework paths while marking actual MoveIt kinematics as unverified.

EngineeringHosted by Vera
Challenge brief

What you are building

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

Parse automated optical inspection defect point clouds for preliminary geometric screening. Triage non-conforming weld assemblies, proposing simulated robot abrasive rework paths while marking actual MoveIt kinematics as unverified.

Robot Cell Process and Welding Engineer

Ingest optical weld seam inspection profiles containing 3D defect coordinate clusters, porosity depths, and simplified operational feed rates.

Perform preliminary geometric screening of 3D defect bounds against explicitly supplied fictional robot reachability radial thresholds.

Classify defects into proposed robot grinding routines, manual repair bench triage, or terminal scrap dispositions based on defect depth.

Synthesize preliminary waypoint coordinates for robot rework trajectories and generate a dossier explicitly marking collision and reachability checks as unverified pending an actual MoveIt solver.

3D coordinate visualizer showing weld seam defect clusters, simplified reachability boundaries, and a disposition summary panel flagging unverified kinematic states.

Generate 200 synthetic weld inspection records containing XYZ defect coordinates, seam lengths, defect depths, and explicitly supplied fictional feed rates and reach thresholds. Starter examples below are synthetic. They are not downloaded records.

MoveIt robotics References MoveIt principles by explicitly deferring actual inverse kinematics and collision avoidance to a dedicated MoveIt solver in downstream steps.

dspy, scipy, fastapi. DSPy provides declarative prompt optimization to reliably translate 3D geometric defect bounds and rules into structured preliminary trajectory planning decisions. Requires spatial reasoning capability via hosted LLM or fine-tuned instruction model to apply explicit geometric rules.

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.

Identifies whether seam coordinates fall inside or outside the defined simplified geometric reachability sphere radius.

Routes seams with excessive defect depth (>3mm) to scrap or manual benches regardless of preliminary reachability.

Outputs a JSON rework trajectory including proposed waypoint offsets, explicitly marking reachability and collision checks as unverified.

```json [ { "input": { "weld_id": "WELD-SEAM-772", "defect_type": "porosity", "defect_depth_mm": 1.4, "coordinates": { "x": 0.45, "y": 0.2, "z": 0.35 }, "fictional_thresholds": { "max_radius_m": 0.85, "min_radius_m": 0.15, "grinding_feed_rate_mm_s": 15 } }, "expected_output": { "weld_id": "WELD-SEAM-772", "preliminary_reachability": "within_radius", "kinematics_verified": false, "triage_decision": "PROPOSED_ROBOT_REWORK", "rework_plan": { "tool_pass": "abrasive_grind", "feed_rate_mm_s": 15, "target_coordinates": { "x": 0.45, "y": 0.2, "z": 0.35 } } } }, { "input": { "weld_id": "WELD-SEAM-910", "defect_type": "burn_through", "defect_depth_mm": 4.2, "coordinates": { "x": 0.95, "y": 0.5, "z": 0.6 }, "fictional_thresholds": { "max_radius_m": 0.85, "min_radius_m": 0.15, "grinding_feed_rate_mm_s": 15 } }, "expected_output": { "weld_id": "WELD-SEAM-910", "preliminary_reachability": "outside_radius", "kinematics_verified": false, "triage_decision": "SCRAP_OR_MANUAL_BENCH", "rework_plan": null } } ] ```

Simulation and offline trajectory generation only; no direct execution on physical robot arm controllers. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Simulation and offline trajectory generation only; no direct execution on physical robot arm controllers. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Identifies whether seam coordinates fall inside or outside the defined simplified geometric reachability sphere radius. Routes seams with excessive defect depth (>3mm) to scrap or manual benches regardless of preliminary reachability. Outputs a JSON rework trajectory including proposed waypoint offsets, explicitly marking reachability and collision checks as unverified.

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 optical weld seam inspection profiles containing 3D defect coordinate clusters, porosity depths, and simplified operational feed rates. Perform preliminary geometric screening of 3D defect bounds against explicitly supplied fictional robot reachability radial thresholds. Classify defects into proposed robot grinding routines, manual repair bench triage, or terminal scrap dispositions based on defect depth. Synthesize preliminary waypoint coordinates for robot rework trajectories and generate a dossier explicitly marking collision and reachability checks as unverified pending an actual MoveIt solver.

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

Identifies whether seam coordinates fall inside or outside the defined simplified geometric reachability sphere radius. Routes seams with excessive defect depth (>3mm) to scrap or manual benches regardless of preliminary reachability. Outputs a JSON rework trajectory including proposed waypoint offsets, explicitly marking reachability and collision checks as unverified.

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

3D coordinate visualizer showing weld seam defect clusters, simplified reachability boundaries, and a disposition summary panel flagging unverified kinematic states.

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

Simulation and offline trajectory generation only; no direct execution on physical robot arm controllers.

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 optical weld seam inspection profiles containing 3D defect coordinate clusters, porosity depths, and simplified operational feed rates.

  • Perform preliminary geometric screening of 3D defect bounds against explicitly supplied fictional robot reachability radial thresholds.

  • Classify defects into proposed robot grinding routines, manual repair bench triage, or terminal scrap dispositions based on defect depth.

  • Synthesize preliminary waypoint coordinates for robot rework trajectories and generate a dossier explicitly marking collision and reachability checks as unverified pending an actual MoveIt solver.

Resources and assets

Reference links and supporting material

Dataset notes

Generate 200 synthetic weld inspection records containing XYZ defect coordinates, seam lengths, defect depths, and explicitly supplied fictional feed rates and reach thresholds. 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 optical weld seam inspection profiles containing 3D defect coordinate clusters, porosity depths, and...
  • Identifies whether seam coordinates fall inside or outside the defined simplified geometric reachability sp...
  • 3D coordinate visualizer showing weld seam defect clusters, simplified reachability boundaries, and a dispo...
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 Weld Optical Inspection Defect Triage Planner