{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:EDJJXGC2AZWKZ5CNSU7RFIM7EX","short_pith_number":"pith:EDJJXGC2","schema_version":"1.0","canonical_sha256":"20d29b985a066cacf44d953f12a19f25e6121644bfb89a48d783f38f0ff2344d","source":{"kind":"arxiv","id":"2109.09903","version":3},"attestation_state":"computed","paper":{"title":"AirDOS: Dynamic SLAM benefits from Articulated Objects","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Chen Wang, Mina Henein, Sebastian Scherer, Wenshan Wang, Yuheng Qiu","submitted_at":"2021-09-21T01:23:48Z","abstract_excerpt":"Dynamic Object-aware SLAM (DOS) exploits object-level information to enable robust motion estimation in dynamic environments. Existing methods mainly focus on identifying and excluding dynamic objects from the optimization. In this paper, we show that feature-based visual SLAM systems can also benefit from the presence of dynamic articulated objects by taking advantage of two observations: (1) The 3D structure of each rigid part of articulated object remains consistent over time; (2) The points on the same rigid part follow the same motion. In particular, we present AirDOS, a dynamic object-aw"},"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":"2109.09903","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-09-21T01:23:48Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2f4ed6c92b9a82a2cde6d55d20b5f909ce05056d4f8d5b760b26734db25bd160","abstract_canon_sha256":"0133eab307d228681bcd95782fe7195ad43832d82cddfd5194d2c2272f22085f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:35.645594Z","signature_b64":"70CO/Oq3OtWncJb0hn9J5r60K6ENpZ4/X9SQjRvVp/goYgh9ef7521cjff2b54BpAZNwxVKEL1NMfS9N71LaCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20d29b985a066cacf44d953f12a19f25e6121644bfb89a48d783f38f0ff2344d","last_reissued_at":"2026-07-05T05:15:35.645167Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:35.645167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AirDOS: Dynamic SLAM benefits from Articulated Objects","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Chen Wang, Mina Henein, Sebastian Scherer, Wenshan Wang, Yuheng Qiu","submitted_at":"2021-09-21T01:23:48Z","abstract_excerpt":"Dynamic Object-aware SLAM (DOS) exploits object-level information to enable robust motion estimation in dynamic environments. Existing methods mainly focus on identifying and excluding dynamic objects from the optimization. In this paper, we show that feature-based visual SLAM systems can also benefit from the presence of dynamic articulated objects by taking advantage of two observations: (1) The 3D structure of each rigid part of articulated object remains consistent over time; (2) The points on the same rigid part follow the same motion. In particular, we present AirDOS, a dynamic object-aw"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.09903","kind":"arxiv","version":3},"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/2109.09903/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":"2109.09903","created_at":"2026-07-05T05:15:35.645229+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.09903v3","created_at":"2026-07-05T05:15:35.645229+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.09903","created_at":"2026-07-05T05:15:35.645229+00:00"},{"alias_kind":"pith_short_12","alias_value":"EDJJXGC2AZWK","created_at":"2026-07-05T05:15:35.645229+00:00"},{"alias_kind":"pith_short_16","alias_value":"EDJJXGC2AZWKZ5CN","created_at":"2026-07-05T05:15:35.645229+00:00"},{"alias_kind":"pith_short_8","alias_value":"EDJJXGC2","created_at":"2026-07-05T05:15:35.645229+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/EDJJXGC2AZWKZ5CNSU7RFIM7EX","json":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX.json","graph_json":"https://pith.science/api/pith-number/EDJJXGC2AZWKZ5CNSU7RFIM7EX/graph.json","events_json":"https://pith.science/api/pith-number/EDJJXGC2AZWKZ5CNSU7RFIM7EX/events.json","paper":"https://pith.science/paper/EDJJXGC2"},"agent_actions":{"view_html":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX","download_json":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX.json","view_paper":"https://pith.science/paper/EDJJXGC2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.09903&json=true","fetch_graph":"https://pith.science/api/pith-number/EDJJXGC2AZWKZ5CNSU7RFIM7EX/graph.json","fetch_events":"https://pith.science/api/pith-number/EDJJXGC2AZWKZ5CNSU7RFIM7EX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX/action/storage_attestation","attest_author":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX/action/author_attestation","sign_citation":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX/action/citation_signature","submit_replication":"https://pith.science/pith/EDJJXGC2AZWKZ5CNSU7RFIM7EX/action/replication_record"}},"created_at":"2026-07-05T05:15:35.645229+00:00","updated_at":"2026-07-05T05:15:35.645229+00:00"}