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The Crop Robot Looked for the Stem It Could Not See

SG-AMP turns uncertain plant geometry into a scene graph that proposes where hidden pepper attachments may be.

Published Updated Story ID: mp-2026-09-02-004
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Summary

SG-AMP turns uncertain plant geometry into a scene graph that proposes where hidden pepper attachments may be.

The system combines depth completion, panoptic mapping and active view planning, then represents peppers, stems and peduncles with different motion costs. Instead of revisiting only uncertain visible regions, it hypothesizes occluded attachments and directs the sensor closer to them. Reported pepper-data results include 55.27% semantic mean intersection over union, 38.67% panoptic quality and 40.62-millimeter depth error.

Why it matters

SG-AMP turns uncertain plant geometry into a scene graph that proposes where hidden pepper attachments may be.

Limits and context

  • Instead of revisiting only uncertain visible regions, it hypothesizes occluded attachments and directs the sensor closer to them.

Key claims

  1. SG-AMP turns uncertain plant geometry into a scene graph that proposes where hidden pepper attachments may be.

    Qualification: Instead of revisiting only uncertain visible regions, it hypothesizes occluded attachments and directs the sensor closer to them.

    Evidence: source-2026-09-02-004

Sources

  1. arXiv preprint 2609.01579arXiv · primary research

Corrections

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