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RQM Sensor Frame Normalization
x402
RQM Sensor Frame Normalization is a paid API for AI agents from jobs.rqmtechnologies.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).
Converts bounded sensor observations from their native coordinate frames into a specified target frame and unit convention using an explicit frame graph.
Price / call$0.01
Success—
StatusUnknown
How this service works
Problem: Convert these bounded sensor observations into the supplied target frame and unit convention. Input: JSON with frame graph, target frame id, observations. Result: normalized or unsupported verdict, normalized observations, transform paths. Limits: Software/model evidence only; 65536 request bytes; 5 s execution.
Output
Returns sensor observations that have been re-expressed in the specified target frame and unit convention, with translations and rotations transformed according to the provided frame graph, handedness, axis convention, and rotation semantics.
Example use cases
Multi-sensor fusion for mobile robot
“I have observations from a front-mounted camera and a side LIDAR, each in their own sensor frames. Using my frame graph that defines both sensors relative to 'odom' with right-handed z-up convention and meters, can you normalize all observations into the 'odom' target frame so I can fuse them?”
Sim-to-real coordinate convention mismatch
“My simulation outputs sensor data in a left-handed y-up frame in centimeters, but my real robot expects right-handed z-up in meters. I have the full frame graph with all transforms defined — can you convert these bounded sensor observations to the 'world' target frame with the correct unit convention?”
Arm end-effector sensor normalization
“I'm getting force-torque sensor readings in the 'wrist_sensor' frame and need them in the 'end_effector' frame for my controller. My frame graph has both frames defined with right-handed axis convention, meters, parent-to-child transforms, and wxyz quaternions — please normalize the observations to 'end_effector'.”
Technical details
Endpoint
POSThttps://jobs.rqmtechnologies.com/x402/buyer-jobs/robotics.normalize-sensor-frames.v1When to prefer
Use this endpoint when you have a fully specified, calibrated frame graph with typed coordinate frames, known rotation semantics, explicit handedness and axis conventions, and a single consistent unit system — and you need bounded sensor observations converted into a target reference frame for downstream robotics processing. Do not use for automatic actuation, unknown transforms, or uncalibrated sensor rigs.
Side effects
- Unknown or missing frame in frame graph returns validation error
- Physically uncalibrated or inconsistent transforms rejected
- Mismatched unit declarations between frames cause rejection
- Malformed quaternion (non-unit norm) or rotation matrix (non-orthogonal) rejected
- Observations referencing frames not present in the graph return lookup error
- Target frame ID not found in the supplied frame graph
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request | object | |
| schema_version | — | |
| idempotency_key | string | |
| max_total_price | string |
Tags
x402
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