Pith Number

pith:QUUXN3ZX

pith:2026:QUUXN3ZXBXA2QAZ3CGOAOFNMGP

not attested not anchored not stored refs pending

Reference-Augmented Learning for Precise Tracking Policy of Tendon-Driven Continuum Robots

Haojian Lu, Ke Qiu, Rong Xiong, Yue Wang, Ziqing Zou

A reference-augmented offline learning method trains control policies that cut average position error by 50.9 percent on tendon-driven continuum robots.

arxiv:2604.25698 v2 · 2026-04-28 · cs.RO

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{QUUXN3ZXBXA2QAZ3CGOAOFNMGP}

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

Experimental results on a three-section TDCR platform demonstrate that the proposed policy achieves a 50.9% reduction in average position error compared to non-augmented baselines and significantly outperforms Jacobian-based methods in both precision and stability across various speeds.

C2weakest assumption

The differentiable RNN-based dynamics surrogate accurately captures the nonlinear, path-dependent, and non-Markovian behavior of the TDCR so that gradients from the augmented reference distribution can reliably optimize a policy that generalizes without further hardware interaction.

C3one line summary

Reference-augmented learning with RNN surrogate and stochastic perturbations cuts average position error by 50.9% for 6-DOF tracking on a three-section TDCR compared to non-augmented baselines.

Receipt and verification

First computed	2026-06-24T01:15:03.179244Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

852976ef370dc1a8033b119c0715ac33ed9a32ac8f16b5c5ec18f18cdf4ce87a

Aliases

arxiv: 2604.25698 · arxiv_version: 2604.25698v2 · doi: 10.48550/arxiv.2604.25698 · pith_short_12: QUUXN3ZXBXA2 · pith_short_16: QUUXN3ZXBXA2QAZ3 · pith_short_8: QUUXN3ZX

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/QUUXN3ZXBXA2QAZ3CGOAOFNMGP \
  | 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: 852976ef370dc1a8033b119c0715ac33ed9a32ac8f16b5c5ec18f18cdf4ce87a

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "f9eb9a4ac98c194f5dc6509e7500aa7bdcfcc56a4bd29fc4021fd26b7e33cb00",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-04-28T14:24:58Z",
    "title_canon_sha256": "8f11f1a5dca4c9cfb99e80391e9ae90c8ee677b91a21719cc0cf2a5337fa33c0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.25698",
    "kind": "arxiv",
    "version": 2
  }
}