Pith Number

pith:M7HLJFI4

pith:2026:M7HLJFI4N7EYGG3SPQKGPOB6O6

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Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees

Jakob Thumm, Marco Pavone, Marian Frei, Matthias Althoff, Tianle Ni

Conformal prediction sets deliver valid high-confidence bounds on human motion predictions for integration into certifiable robot safety systems.

arxiv:2604.15221 v2 · 2026-04-16 · cs.RO · cs.CV

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We propose conformal prediction sets for human motion predictions with high, valid confidence that can be integrated into certifiable safety frameworks for human-robot collaboration.

C2weakest assumption

The assumption that the conformal prediction sets remain valid when deployed in real-world human-robot settings, which requires the test distribution of human motions to be sufficiently similar to the calibration data used to construct the sets.

C3one line summary

Proposes a vision-based human pose estimation and motion prediction pipeline that uses conformal prediction sets to provide valid confidence guarantees for safe human-robot collaboration.

References

36 extracted · 36 resolved · 0 Pith anchors

[1] On making robots understand safety: Embedding injury knowledge into control, 2012

[2] Online verification of multiple safety criteria for a robot trajectory, 2017

[3] Provably safe deep reinforcement learning for robotic manipulation in human environments, 2022

[4] A general safety framework for autonomous manipulation in human environments, 2026

[5] Safety in human-robot collaborative manufacturing environments: Metrics and control, 2016

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:00:38.183208Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

67ceb4951c6fc9831b727c1467b83e7780566fbca0ac5c31a69247e122a2f233

Aliases

arxiv: 2604.15221 · arxiv_version: 2604.15221v2 · doi: 10.48550/arxiv.2604.15221 · pith_short_12: M7HLJFI4N7EY · pith_short_16: M7HLJFI4N7EYGG3S · pith_short_8: M7HLJFI4

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/M7HLJFI4N7EYGG3SPQKGPOB6O6 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 67ceb4951c6fc9831b727c1467b83e7780566fbca0ac5c31a69247e122a2f233

Canonical record JSON

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    "abstract_canon_sha256": "7d527f290c7f9b5552b01cced44275f20c51320d2c03f1dd7aa91b4384cb907a",
    "cross_cats_sorted": [
      "cs.CV"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-04-16T16:53:26Z",
    "title_canon_sha256": "d1aadb6bdc224bcd1acbfa938742238fe587bf7d8f42dd704c48a8a41960f20a"
  },
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  "source": {
    "id": "2604.15221",
    "kind": "arxiv",
    "version": 2
  }
}