pith:66Z3HHJO
Adaptive Modular Geometric Control of Robotic Manipulators
Decomposing manipulator dynamics into modules enables local geometric controllers with a single adaptation gain that cut RMS position error by at least 12.2 percent.
arxiv:2603.03965 v3 · 2026-03-04 · eess.SY · cs.SY
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Claims
The proposed adaptive modular geometric control framework reduces the RMS position error by at least 12.2% compared with state-of-the-art controllers under almost the same control effort, while the nominal case establishes exponential stability.
The overall manipulator dynamics can be decomposed into individual modules such that local geometric control laws can be designed independently while still guaranteeing global stability and performance.
An adaptive modular geometric controller for robotic manipulators achieves exponential stability in nominal cases and reduces RMS position error by at least 12.2% versus state-of-the-art methods in simulations while using similar effort.
Receipt and verification
| First computed | 2026-06-19T16:09:55.885099Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f7b3b39d2e896d31dc3be5a889bcfe6945ed218041cdd7770b98ea75412dff21
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/66Z3HHJORFWTDXB34WUITPH6NF \
| 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())"
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Canonical record JSON
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