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Challenge

Build a Robot-Cell Payload Inertia Validation Engine

Inspect dynamic payload weight and inertia matrix estimates against MoveIt robot kinematic limits. Flag parameter drift and synthesize joint torque limit adjustments to ensure mechanical safety before initiating high-speed production runs.

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Challenge brief

What you are building

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

Inspect dynamic payload weight and inertia matrix estimates against MoveIt robot kinematic limits. Flag parameter drift and synthesize joint torque limit adjustments to ensure mechanical safety before initiating high-speed production runs.

Robotics Calibration Engineer

Ingest estimated 6-DOF payload inertia matrices, payload mass, and center of mass offsets.

Calculate expected joint torques during maximum acceleration using MoveIt dynamic models.

Determine whether required joint torques exceed actuator limits based on payload configurations.

Synthesize validated payload parameters and generate a dynamic safety sign-off sheet for controllers.

Dynamic payload viewer displaying center of mass offsets, joint torque utilization charts, and sign-off forms.

Simulated dynamic payload parameter JSON records (simplified synthetic app records, not complete official schema files). Starter examples below are synthetic. They are not downloaded records.

MoveIt robotics MoveIt dynamics and kinematic limits from moveit_core to evaluate joint limits.

ray-serve, pydantic, numpy. Serves high-throughput joint torque calculations across multi-robot production lines via scalable endpoints. Local model for fast mathematical validation or hosted LLM for generating dynamic sign-off certificates.

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.

Computes expected maximum joint torque exactly as (payload_mass_kg * peak_acceleration_rad_s2 * com_offset_x_m).

Rejects payload configurations where computed max torque strictly exceeds max_torque_limit_nm.

Outputs validated payload status and required torque constraints for the safety review team.

```json [ { "input": { "robot_id": "ROBOT-PALLET-01", "payload_mass_kg": 25, "com_offset_x_m": 0.1, "peak_acceleration_rad_s2": 15, "max_torque_limit_nm": 50 }, "expected_output": { "max_torque_required_nm": 37.5, "within_limits": true, "status": "DYNAMICS_ACCEPTED" } }, { "input": { "robot_id": "ROBOT-PALLET-01", "payload_mass_kg": 45, "com_offset_x_m": 0.3, "peak_acceleration_rad_s2": 15, "max_torque_limit_nm": 150 }, "expected_output": { "max_torque_required_nm": 202.5, "within_limits": false, "status": "EXCEEDS_TORQUE_LIMITS" } } ] ```

Read-only dynamics evaluation; torque configurations are reviewed and manually confirmed before writing to hardware. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Read-only dynamics evaluation; torque configurations are reviewed and manually confirmed before writing to hardware. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Computes expected maximum joint torque exactly as (payload_mass_kg * peak_acceleration_rad_s2 * com_offset_x_m). Rejects payload configurations where computed max torque strictly exceeds max_torque_limit_nm. Outputs validated payload status and required torque constraints for the safety review team.

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 estimated 6-DOF payload inertia matrices, payload mass, and center of mass offsets. Calculate expected joint torques during maximum acceleration using MoveIt dynamic models. Determine whether required joint torques exceed actuator limits based on payload configurations. Synthesize validated payload parameters and generate a dynamic safety sign-off sheet for controllers.

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

Computes expected maximum joint torque exactly as (payload_mass_kg * peak_acceleration_rad_s2 * com_offset_x_m). Rejects payload configurations where computed max torque strictly exceeds max_torque_limit_nm. Outputs validated payload status and required torque constraints for the safety review team.

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

Dynamic payload viewer displaying center of mass offsets, joint torque utilization charts, and sign-off forms.

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 dynamics evaluation; torque configurations are reviewed and manually confirmed before writing to hardware.

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 estimated 6-DOF payload inertia matrices, payload mass, and center of mass offsets.

  • Calculate expected joint torques during maximum acceleration using MoveIt dynamic models.

  • Determine whether required joint torques exceed actuator limits based on payload configurations.

  • Synthesize validated payload parameters and generate a dynamic safety sign-off sheet for controllers.

Resources and assets

Reference links and supporting material

Dataset notes

Simulated dynamic payload parameter JSON records (simplified synthetic app records, not complete official schema files). Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Ray Serve

Action Space in the agent workflow.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest estimated 6-DOF payload inertia matrices, payload mass, and center of mass offsets. Calculate expect...
  • Computes expected maximum joint torque exactly as (payload_mass_kg * peak_acceleration_rad_s2 * com_offset_...
  • Dynamic payload viewer displaying center of mass offsets, joint torque utilization charts, and sign-off forms.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 1 configured tool

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
  • Ray Serve · 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 Payload Inertia Validation Engine