{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:ZLIOBN3E5RPV73XVW6UVYBZ5MS","short_pith_number":"pith:ZLIOBN3E","schema_version":"1.0","canonical_sha256":"cad0e0b764ec5f5feef5b7a95c073d6485100517d52f828b577488f4dda2d502","source":{"kind":"arxiv","id":"2512.12649","version":2},"attestation_state":"computed","paper":{"title":"Bayesian Optimization Parameter Tuning Framework for a Lyapunov Based Path Following Controller","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Hongkang Yu, Mo Chen, Takashi Suzuki, Wenjing Cao, Zhewen Zheng","submitted_at":"2025-12-14T11:35:53Z","abstract_excerpt":"Parameter tuning in real-world experiments is constrained by the limited evaluation budget available on hardware. The path-following controller studied in this paper reflects a typical situation in nonlinear geometric controller, where multiple gains influence the dynamics through coupled nonlinear terms. Such interdependence makes manual tuning inefficient and unlikely to yield satisfactory performance within a practical number of trials. To address this challenge, we propose a Bayesian optimization (BO) framework that treats the closed-loop system as a black box and selects controller gains "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2512.12649","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-12-14T11:35:53Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"526e45872d412eeb521cb3abbbc1cdeef1a077c3fae7719d99b27dc4300d0afc","abstract_canon_sha256":"56c03f95c1ffce5246a708ffa4d7ff0d4bf4bc694230f077042c6227bd7975ce"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T02:04:44.776127Z","signature_b64":"9bYa3/VrjvTR9g1MU328GLriZspGOSiQ7erso3KI5Eko9Kcto3vEIzN8loqYfpTmuJ1nTx2cXL/af1QZn26RAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cad0e0b764ec5f5feef5b7a95c073d6485100517d52f828b577488f4dda2d502","last_reissued_at":"2026-05-28T02:04:44.775583Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T02:04:44.775583Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian Optimization Parameter Tuning Framework for a Lyapunov Based Path Following Controller","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Hongkang Yu, Mo Chen, Takashi Suzuki, Wenjing Cao, Zhewen Zheng","submitted_at":"2025-12-14T11:35:53Z","abstract_excerpt":"Parameter tuning in real-world experiments is constrained by the limited evaluation budget available on hardware. The path-following controller studied in this paper reflects a typical situation in nonlinear geometric controller, where multiple gains influence the dynamics through coupled nonlinear terms. Such interdependence makes manual tuning inefficient and unlikely to yield satisfactory performance within a practical number of trials. To address this challenge, we propose a Bayesian optimization (BO) framework that treats the closed-loop system as a black box and selects controller gains "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2512.12649","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2512.12649/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2512.12649","created_at":"2026-05-28T02:04:44.775647+00:00"},{"alias_kind":"arxiv_version","alias_value":"2512.12649v2","created_at":"2026-05-28T02:04:44.775647+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2512.12649","created_at":"2026-05-28T02:04:44.775647+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZLIOBN3E5RPV","created_at":"2026-05-28T02:04:44.775647+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZLIOBN3E5RPV73XV","created_at":"2026-05-28T02:04:44.775647+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZLIOBN3E","created_at":"2026-05-28T02:04:44.775647+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS","json":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS.json","graph_json":"https://pith.science/api/pith-number/ZLIOBN3E5RPV73XVW6UVYBZ5MS/graph.json","events_json":"https://pith.science/api/pith-number/ZLIOBN3E5RPV73XVW6UVYBZ5MS/events.json","paper":"https://pith.science/paper/ZLIOBN3E"},"agent_actions":{"view_html":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS","download_json":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS.json","view_paper":"https://pith.science/paper/ZLIOBN3E","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2512.12649&json=true","fetch_graph":"https://pith.science/api/pith-number/ZLIOBN3E5RPV73XVW6UVYBZ5MS/graph.json","fetch_events":"https://pith.science/api/pith-number/ZLIOBN3E5RPV73XVW6UVYBZ5MS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS/action/storage_attestation","attest_author":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS/action/author_attestation","sign_citation":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS/action/citation_signature","submit_replication":"https://pith.science/pith/ZLIOBN3E5RPV73XVW6UVYBZ5MS/action/replication_record"}},"created_at":"2026-05-28T02:04:44.775647+00:00","updated_at":"2026-05-28T02:04:44.775647+00:00"}