What Six Months of Warehouse Robot Failures Taught Us

Over six months monitoring a fleet of 40 warehouse robots across three facilities, we expected localization drift to dominate the failure log. It didn't.

The largest single category — just under a third of all incidents — came from map staleness: pallets, temporary racking, and seasonal layout changes that outpaced the fleet's shared map update cycle. The robots weren't wrong about where they were. They were right about a warehouse that no longer existed.

This reframes the reliability problem. Better SLAM doesn't fix a stale map. What fixes it is treating the map itself as a perishable artifact with its own freshness guarantees, monitored the way you'd monitor a cache.

We're folding this into the next revision of the Failure Atlas as its own root-cause category: environment-model divergence, distinct from sensor-level localization error.