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AI agent for robotics engineers

Perception Failure Replay Agent

Reproduce a perception failure, fix it, and prove that earlier cases still pass

Quality controlAutomationIT and developmentProduct development
See how it worksGet access
Perception Failure Replay Agent: what goes in, what the agent does and what you get

What it does

A robot misses a pallet or confuses a shadow for an obstacle, and nobody can reproduce it because the scene is gone. This agent collects the logs around the failure: camera or lidar frames, odometry, parameters and software version. It replays the sensor data through the same perception code in simulation to see if the failure reproduces. Once it does, it tests parameter changes or algorithm settings against the same recording. Next it reruns a library of earlier logs to check that nothing else got worse. If a fix helps this case but breaks others, it tries another. The engineer approves the change before it goes onto the robot. Edge case: the failure does not reproduce in replay, so the agent checks timing and clock drift in the recording.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueYes, continueApprovedNoNoNo 1 STARTS WHEN Failure reported with time and robot 2 USES A TOOL Collect logs and sensor data around the failure 3 USES A TOOL Replay the data through the perception code 4 CHECKS THE RESULT Does the failure reproduce in replay? If not: check timestamps, clock drift and softwareversion, and collect a longer window. Back to step 2. 5 DOES Propose parameter or setting changes 6 USES A TOOL Replay the failing log with each change 7 CHECKS THE RESULT Does the failing case pass? If not: try the next change. Back to step 5. 8 USES A TOOL Run the regression log library with the winningchange 9 CHECKS THE RESULT Is the regression pass rate within 1% of before? If not: reject the change and try another. Back to step5. 10 YOU APPROVE Engineer approves the change for the robot 11 RESULT Failure report with the fix and regression results
Read the steps as a list
  1. Failure reported with time and robot
  2. Collect logs and sensor data around the failure
  3. Replay the data through the perception code
  4. Does the failure reproduce in replay?If not: check timestamps, clock drift and software version, and collect a longer window. Back to step 2.
  5. Propose parameter or setting changes
  6. Replay the failing log with each change
  7. Does the failing case pass?If not: try the next change. Back to step 5.
  8. Run the regression log library with the winning change
  9. Is the regression pass rate within 1% of before?If not: reject the change and try another. Back to step 5.
  10. Engineer approves the change for the robotThe agent waits here for your OK.
  11. Failure report with the fix and regression results

How it decides

It accepts a change only if the failing case passes and the pass rate on the regression library stays within the allowed drop.

  • Replay with the exact software and parameter version first
  • Change one parameter per test
  • Reject a fix that lowers the regression pass rate by more than 1%
  • Add the failing log to the regression library

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Regression library location
  • Allowed drop in pass rate (default 1%)
  • Log window size (default 60 seconds)
  • Parameters allowed to change
  • Simulator used

What keeps you in control

It always asks you first

  • Engineer approves the change for deployment
  • Safety lead approves changes to obstacle detection

Hard limits

  • Never deploy to a robot without approval
  • Never remove a safety detection to fix a false stop

It stops when

  • Done: the failure is fixed and regression results are held
  • Stop: the failure cannot be reproduced after a longer window

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA warehouse robot stopped for a shadow on the floor. Replay of 40 seconds of lidar did not show it, so the first check failed. The agent found the recording lacked camera exposure data and asked for the longer log. It reproduced then. Raising the depth confidence cutoff fixed it, but dropped regression passes from 98% to 94%. A smaller change kept 97.6% and the engineer approved.

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