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    "headline": "Robot Skin Learned Its Own Layout",
    "slug": "robot-skin-learned-its-own-layout",
    "dek": "A self-supervised encoder used sparse sensor geometry to learn touch signals.",
    "summary": "A self-supervised encoder used sparse sensor geometry to learn touch signals.",
    "body_text": "Tactile-JEPA predicts masked sensor embeddings from the remaining signals while using the connectivity of distributed electronic skin to guide masking. The authors argue that irregular tactile layouts call for different pretraining from image encoders. Their evaluations probe representation quality for touch sensing; the paper does not establish a general-purpose robot hand.",
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      "Their evaluations probe representation quality for touch sensing; the paper does not establish a general-purpose robot hand."
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    "tags": [
      "tactile sensing",
      "robot skin"
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    "image_url": null,
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      "source_id": "source-2026-09-22-018",
      "title": "arXiv preprint 2609.24385",
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      "published_at": "2026-09-21T06:22:06.000-04:00",
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    "title": "Robot Skin Learned Its Own Layout",
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