{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:MHTQ24S43FTNYATRSBRPV7JB6C","short_pith_number":"pith:MHTQ24S4","schema_version":"1.0","canonical_sha256":"61e70d725cd966dc02719062fafd21f0ac53eb5593af166b2adc45627c0a213b","source":{"kind":"arxiv","id":"1702.03435","version":1},"attestation_state":"computed","paper":{"title":"Distributed Mapping with Privacy and Communication Constraints: Lightweight Algorithms and Object-based Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Carlos Nieto, Frank Dellaert, Henrik I. Christensen, John Rogers, Luca Carlone, Siddharth Choudhary","submitted_at":"2017-02-11T16:08:22Z","abstract_excerpt":"We consider the following problem: a team of robots is deployed in an unknown environment and it has to collaboratively build a map of the area without a reliable infrastructure for communication. The backbone for modern mapping techniques is pose graph optimization, which estimates the trajectory of the robots, from which the map can be easily built. The first contribution of this paper is a set of distributed algorithms for pose graph optimization: rather than sending all sensor data to a remote sensor fusion server, the robots exchange very partial and noisy information to reach an agreemen"},"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":"1702.03435","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2017-02-11T16:08:22Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"fb1969234a432f89c5a7cff63f74d13f675e45306037229f5ed201a27db63ec7","abstract_canon_sha256":"0db2dc9a532b63cedfc27c56b43a647b791501663b095cac49a5eff981cad5df"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:53.792021Z","signature_b64":"YIYKL+XlufXlhlPSeAePJD2H6dA5mfbfD2I52Iz0e9nDv1192wkJgwX3llyqF5iRGOSxRo/T/EJlDrg12sGiCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61e70d725cd966dc02719062fafd21f0ac53eb5593af166b2adc45627c0a213b","last_reissued_at":"2026-05-18T00:50:53.791539Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:53.791539Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributed Mapping with Privacy and Communication Constraints: Lightweight Algorithms and Object-based Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Carlos Nieto, Frank Dellaert, Henrik I. Christensen, John Rogers, Luca Carlone, Siddharth Choudhary","submitted_at":"2017-02-11T16:08:22Z","abstract_excerpt":"We consider the following problem: a team of robots is deployed in an unknown environment and it has to collaboratively build a map of the area without a reliable infrastructure for communication. The backbone for modern mapping techniques is pose graph optimization, which estimates the trajectory of the robots, from which the map can be easily built. The first contribution of this paper is a set of distributed algorithms for pose graph optimization: rather than sending all sensor data to a remote sensor fusion server, the robots exchange very partial and noisy information to reach an agreemen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.03435","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1702.03435","created_at":"2026-05-18T00:50:53.791612+00:00"},{"alias_kind":"arxiv_version","alias_value":"1702.03435v1","created_at":"2026-05-18T00:50:53.791612+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.03435","created_at":"2026-05-18T00:50:53.791612+00:00"},{"alias_kind":"pith_short_12","alias_value":"MHTQ24S43FTN","created_at":"2026-05-18T12:31:31.346846+00:00"},{"alias_kind":"pith_short_16","alias_value":"MHTQ24S43FTNYATR","created_at":"2026-05-18T12:31:31.346846+00:00"},{"alias_kind":"pith_short_8","alias_value":"MHTQ24S4","created_at":"2026-05-18T12:31:31.346846+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/MHTQ24S43FTNYATRSBRPV7JB6C","json":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C.json","graph_json":"https://pith.science/api/pith-number/MHTQ24S43FTNYATRSBRPV7JB6C/graph.json","events_json":"https://pith.science/api/pith-number/MHTQ24S43FTNYATRSBRPV7JB6C/events.json","paper":"https://pith.science/paper/MHTQ24S4"},"agent_actions":{"view_html":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C","download_json":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C.json","view_paper":"https://pith.science/paper/MHTQ24S4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1702.03435&json=true","fetch_graph":"https://pith.science/api/pith-number/MHTQ24S43FTNYATRSBRPV7JB6C/graph.json","fetch_events":"https://pith.science/api/pith-number/MHTQ24S43FTNYATRSBRPV7JB6C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C/action/storage_attestation","attest_author":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C/action/author_attestation","sign_citation":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C/action/citation_signature","submit_replication":"https://pith.science/pith/MHTQ24S43FTNYATRSBRPV7JB6C/action/replication_record"}},"created_at":"2026-05-18T00:50:53.791612+00:00","updated_at":"2026-05-18T00:50:53.791612+00:00"}