pith. sign in
Pith Number

pith:5YASPIOR

pith:2026:5YASPIORTRTIQY2SBUV372WZDT
not attested not anchored not stored refs resolved

Robot Squid Game: Quadrupedal Locomotion for Traversing Narrow Tunnels

Amir Hossain Raj, Dibyendu Das, Xuesu Xiao

Quadruped robots learn to traverse narrow tunnels by distilling specialized policies from procedurally generated environments into one unified policy.

arxiv:2605.13665 v1 · 2026-05-13 · cs.RO

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{5YASPIORTRTIQY2SBUV372WZDT}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
Portable graph bundle live · download bundle · merged state
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

By synthesizing diverse tunnel structures during training and distilling navigation strategies into a generalizable policy our method achieves consistent traversal across complex spatial constraints where conventional approaches fail.

C2weakest assumption

The assumption that policies trained on procedurally generated tunnel geometries will transfer effectively to real-world tunnel configurations without further adaptation or domain randomization beyond what is described.

C3one line summary

A teacher-student RL policy distillation approach combined with procedural tunnel generation enables quadruped robots to traverse narrow tunnels consistently in both simulation and real-world tests.

References

26 extracted · 26 resolved · 1 Pith anchors

[1] Learning to navigate sidewalks in outdoor environments, 2022
[2] Bark- our: Benchmarking animal-level agility with quadruped robots.arXiv preprint arXiv:2305.14654, 2023 2023
[3] Learning quadrupedal locomotion over challenging terrain, 2020
[4] Rma: Rapid motor adaptation for legged robots 2021
[5] Learning dynamic bipedal walking across stepping stones, 2022
Receipt and verification
First computed 2026-05-18T02:44:17.264799Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

ee0127a1d19c668863520d2bbfead91cf64eb1709d17d13cbc079e436228129e

Aliases

arxiv: 2605.13665 · arxiv_version: 2605.13665v1 · doi: 10.48550/arxiv.2605.13665 · pith_short_12: 5YASPIORTRTI · pith_short_16: 5YASPIORTRTIQY2S · pith_short_8: 5YASPIOR
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5YASPIORTRTIQY2SBUV372WZDT \
  | 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: ee0127a1d19c668863520d2bbfead91cf64eb1709d17d13cbc079e436228129e
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "a37a77f762a7c42656faac8478a885e43fdba7e735faf89cb324c80358cf7bae",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-13T15:22:18Z",
    "title_canon_sha256": "0201fcdc2225428a118f75c873869a681480dd96b378cb6064b87e7fb652f5fa"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13665",
    "kind": "arxiv",
    "version": 1
  }
}