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RQM Reconstruct Smoothed Trajectory
x402
RQM Reconstruct Smoothed Trajectory is a paid API for AI agents from jobs.rqmtechnologies.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Applies a centered moving-average smoothing model to a bounded sequence of timestamped numeric poses and returns the reconstructed trajectory with residual analysis.
Price / call$0.01
Success—
StatusUnknown
How this service works
Problem: Reconstruct this bounded trajectory under the supplied smoothing model and residual rule. Input: JSON with samples, model, rules. Result: smoothed trajectory, residual RMSE, caller-rule verdict. Limits: Software/model evidence only; 65536 request bytes; 5 s execution.
Output
Returns the reconstructed smoothed trajectory as an array of timestamped pose vectors after applying the centered moving-average filter, along with residual information and RMSE metrics indicating how closely the smoothed output fits the original samples within the specified bounds.
Example use cases
Denoise recorded robot motion path
“I recorded a robot arm's end-effector path but it's really jittery from sensor noise. Can you reconstruct a smoothed version using a centered moving-average with a window of 7 samples and a max RMSE of 0.05? Here are the 200 timestamped 6-DOF pose samples.”
Pre-process trajectory before kinematic validation
“Before I validate this drone flight trajectory against kinematic limits, I need to smooth it first. Apply a centered moving-average with a 9-sample window and maximum RMSE of 0.1 to these 512 timestamped position samples spanning 0 to 60 seconds.”
Smooth mobile robot localization estimates
“My SLAM system outputs noisy pose estimates — can you reconstruct a smoothed trajectory from these 300 timestamped 2D pose samples using a 5-sample centered moving-average window with a max RMSE of 0.03?”
Technical details
Endpoint
POSThttps://jobs.rqmtechnologies.com/x402/buyer-jobs/robotics.reconstruct-smoothed-trajectory.v1When to prefer
Use this endpoint when you have a bounded sequence of timestamped numeric pose samples (up to 4096, up to 12 dimensions each) and need to apply a centered moving-average smoothing model with explicit RMSE constraints. It is ideal for pre-processing noisy robot or sensor trajectories before kinematic validation or motion planning. Do not use it to synthesize or interpolate missing data, extrapolate motion, or certify physical feasibility of a trajectory.
Side effects
- RMSE exceeds the specified maximum_rmse threshold — reconstruction rejected with a constraint violation error
- Fewer than 2 samples provided — request rejected as below minimum sample count
- More than 4096 samples provided — request rejected as above maximum sample count
- Window size outside 1–31 range — validation error returned
- Pose vector dimension exceeds 12 — validation error on values array
- Timestamp outside 0–86400 second range — validation error
- Duplicate or out-of-order timestamps — may cause undefined smoothing behavior
- Payment not provided or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request | object | |
| schema_version | — | |
| idempotency_key | string | |
| max_total_price | string |
Tags
x402
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