Belief Consistency Between Foundation-Model Evidence and Geometric Perception in Persistent Robotic Maps
Persistent maps used by autonomous robots increasingly fuse a geometric perception stack whose assertions are well-characterized with a foundation-model channel that produces semantic claims without calibrated reliability about the same scene. Contemporary mapping systems integrate the two channels by treating the foundation-model channel as an additional voter into a per-element posterior, uncalibrated for its own per-class reliability and without machinery to flag when the two channels contradict each other at a given moment. We propose an update operator with two cooperating mechanisms: a per-class calibrated commit gate, and a per-event conflict-drop window that refuses to commit foun...
| Authors | Christoffer Heckman, Harel Biggie, Brendan Crowe et al. |
|---|---|
| Primary category | cs.RO |
| Published | 29 May 2026 |
| Last updated at source | 29 May 2026 |
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