{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:CVKXM77N2N47XKLVAOL6M5JO53","short_pith_number":"pith:CVKXM77N","canonical_record":{"source":{"id":"1903.05355","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-03-13T08:33:46Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"ed6b0db161d6c0404d648c2653dcc5fb3d6b7b954290b6cc0df5751c8b6500aa","abstract_canon_sha256":"6f84aac55aac0c58cabd83ec3c4577abaff1007ca21c70dd236b98e2dab621c2"},"schema_version":"1.0"},"canonical_sha256":"1555767fedd379fba9750397e6752eeec1e4642f9155f4493ed1dcb0fa504a38","source":{"kind":"arxiv","id":"1903.05355","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05355","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05355v1","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05355","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"CVKXM77N2N47","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"CVKXM77N2N47XKLV","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"CVKXM77N","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:CVKXM77N2N47XKLVAOL6M5JO53","target":"record","payload":{"canonical_record":{"source":{"id":"1903.05355","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-03-13T08:33:46Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"ed6b0db161d6c0404d648c2653dcc5fb3d6b7b954290b6cc0df5751c8b6500aa","abstract_canon_sha256":"6f84aac55aac0c58cabd83ec3c4577abaff1007ca21c70dd236b98e2dab621c2"},"schema_version":"1.0"},"canonical_sha256":"1555767fedd379fba9750397e6752eeec1e4642f9155f4493ed1dcb0fa504a38","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:24.550328Z","signature_b64":"Ee+b8R14nIbUCuIg0YKDYWOtyjjM3BEg0JhsXkcVut82RtxeT+qVQi/qQkTMlHrynVdHJ1Z3TwKFtAACPy0MDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1555767fedd379fba9750397e6752eeec1e4642f9155f4493ed1dcb0fa504a38","last_reissued_at":"2026-05-17T23:51:24.549702Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:24.549702Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.05355","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FrHgSpO/WYLCG6+eX+78xt49OKVlTr0k60vrSLhJVsCZqfC8975ZTGtFLBvPEf6N+oM/TaUWC2Wf8aFm4f7ZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T10:33:36.402093Z"},"content_sha256":"a0153b72fa0fe77a2925e62bdf70bbf3114195c7110d147aff5b236189520b78","schema_version":"1.0","event_id":"sha256:a0153b72fa0fe77a2925e62bdf70bbf3114195c7110d147aff5b236189520b78"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:CVKXM77N2N47XKLVAOL6M5JO53","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Framework for On-line Learning of Underwater Vehicles Dynamic Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY"],"primary_cat":"cs.RO","authors_text":"Bilal Wehbe, Frank Kirchner, Marc Hildebrandt","submitted_at":"2019-03-13T08:33:46Z","abstract_excerpt":"Learning the dynamics of robots from data can help achieve more accurate tracking controllers, or aid their navigation algorithms. However, when the actual dynamics of the robots change due to external conditions, on-line adaptation of their models is required to maintain high fidelity performance. In this work, a framework for on-line learning of robot dynamics is developed to adapt to such changes. The proposed framework employs an incremental support vector regression method to learn the model sequentially from data streams. In combination with the incremental learning, strategies for inclu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05355","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gw+lk0qLRfP/M2K05W8Q7AqipBKmu4+GIgizvWdUDYMOCMDrbEczoW4hR0zESNvVkirgZuje8kaCnh86SZHSCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T10:33:36.402444Z"},"content_sha256":"cde510349acae081220843cb90b1dea467357cec281c32aae011d9edb32920e3","schema_version":"1.0","event_id":"sha256:cde510349acae081220843cb90b1dea467357cec281c32aae011d9edb32920e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CVKXM77N2N47XKLVAOL6M5JO53/bundle.json","state_url":"https://pith.science/pith/CVKXM77N2N47XKLVAOL6M5JO53/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CVKXM77N2N47XKLVAOL6M5JO53/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-28T10:33:36Z","links":{"resolver":"https://pith.science/pith/CVKXM77N2N47XKLVAOL6M5JO53","bundle":"https://pith.science/pith/CVKXM77N2N47XKLVAOL6M5JO53/bundle.json","state":"https://pith.science/pith/CVKXM77N2N47XKLVAOL6M5JO53/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CVKXM77N2N47XKLVAOL6M5JO53/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:CVKXM77N2N47XKLVAOL6M5JO53","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"6f84aac55aac0c58cabd83ec3c4577abaff1007ca21c70dd236b98e2dab621c2","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-03-13T08:33:46Z","title_canon_sha256":"ed6b0db161d6c0404d648c2653dcc5fb3d6b7b954290b6cc0df5751c8b6500aa"},"schema_version":"1.0","source":{"id":"1903.05355","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05355","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05355v1","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05355","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"CVKXM77N2N47","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"CVKXM77N2N47XKLV","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"CVKXM77N","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:cde510349acae081220843cb90b1dea467357cec281c32aae011d9edb32920e3","target":"graph","created_at":"2026-05-17T23:51:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Learning the dynamics of robots from data can help achieve more accurate tracking controllers, or aid their navigation algorithms. However, when the actual dynamics of the robots change due to external conditions, on-line adaptation of their models is required to maintain high fidelity performance. In this work, a framework for on-line learning of robot dynamics is developed to adapt to such changes. The proposed framework employs an incremental support vector regression method to learn the model sequentially from data streams. In combination with the incremental learning, strategies for inclu","authors_text":"Bilal Wehbe, Frank Kirchner, Marc Hildebrandt","cross_cats":["cs.LG","cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-03-13T08:33:46Z","title":"A Framework for On-line Learning of Underwater Vehicles Dynamic Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05355","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:a0153b72fa0fe77a2925e62bdf70bbf3114195c7110d147aff5b236189520b78","target":"record","created_at":"2026-05-17T23:51:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"6f84aac55aac0c58cabd83ec3c4577abaff1007ca21c70dd236b98e2dab621c2","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-03-13T08:33:46Z","title_canon_sha256":"ed6b0db161d6c0404d648c2653dcc5fb3d6b7b954290b6cc0df5751c8b6500aa"},"schema_version":"1.0","source":{"id":"1903.05355","kind":"arxiv","version":1}},"canonical_sha256":"1555767fedd379fba9750397e6752eeec1e4642f9155f4493ed1dcb0fa504a38","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1555767fedd379fba9750397e6752eeec1e4642f9155f4493ed1dcb0fa504a38","first_computed_at":"2026-05-17T23:51:24.549702Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:24.549702Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ee+b8R14nIbUCuIg0YKDYWOtyjjM3BEg0JhsXkcVut82RtxeT+qVQi/qQkTMlHrynVdHJ1Z3TwKFtAACPy0MDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:24.550328Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.05355","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0153b72fa0fe77a2925e62bdf70bbf3114195c7110d147aff5b236189520b78","sha256:cde510349acae081220843cb90b1dea467357cec281c32aae011d9edb32920e3"],"state_sha256":"3915d262b0fc053a7e173c34a1b00ad91af4d039ba4254627c16490f87b7b808"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7ugGlQxO8uFkmGa2SEcY9NdmVgukBluj3iBZAcVHmCpdNLrmAnXEIYh/b8sRBurKISyuCHGzer7CYGOys0RIDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T10:33:36.404361Z","bundle_sha256":"2becdaa74532afcd76e999aa748711c9685d6cede945c44b6dc6758294e7cf73"}}