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pith:2026:X4FJKXA35PU4N5XHSK2TQOO6B7
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NORM-Nav: Zero-Shot Mobile Robot Navigation with Natural Language Behavioral Constraints

Chao Gao, Dongjie Huo, Dong Zhang, Guyue Zhou, Junhui Wang, Yan Qiao

NORM-Nav converts natural language behavioral constraints into multi-layer costmaps that standard planners can use for more human-like robot paths.

arxiv:2605.16979 v1 · 2026-05-16 · cs.RO

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4 Citations open
5 Replications open
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Claims

C1strongest claim

NORM-Nav improves task success rates and produces trajectories closer to human references than representative baselines in simulation and real-world experiments.

C2weakest assumption

The LLM can reliably parse natural language behavioral constraints and the real-time vision-LiDAR system can accurately ground those constraints to produce effective multi-layer costmaps that preserve intended behavior when used by standard planners.

C3one line summary

NORM-Nav is a zero-shot framework that parses natural language behavioral constraints with an LLM, grounds them via vision-LiDAR, and encodes them as multi-layer costmaps for grid-based robot navigation.

References

32 extracted · 32 resolved · 4 Pith anchors

[1] Safe-vln: Collision avoidance for vision-and-language navigation of autonomous robots operating in continuous environments, 2024
[2] MPC-DS: A safe path track- ing method for agvs in dynamic environments with dense obstacles, 2025
[3] Openbench: A new benchmark and baseline for semantic navigation in smart logistics, 2025
[4] Open: Lightweight map-based semantic navigation for gps-free last-mile delivery, 2025
[5] The marathon 2: A navigation system, 2020

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Receipt and verification
First computed 2026-05-20T00:03:34.207975Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

bf0a955c1bebe9c6f6e792b53839de0fce9cb26817f405014efe71ab02b58908

Aliases

arxiv: 2605.16979 · arxiv_version: 2605.16979v1 · doi: 10.48550/arxiv.2605.16979 · pith_short_12: X4FJKXA35PU4 · pith_short_16: X4FJKXA35PU4N5XH · pith_short_8: X4FJKXA3
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/X4FJKXA35PU4N5XHSK2TQOO6B7 \
  | 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: bf0a955c1bebe9c6f6e792b53839de0fce9cb26817f405014efe71ab02b58908
Canonical record JSON
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