{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:WQPXP4PIRLCIRKKQJ7YMKBVU36","short_pith_number":"pith:WQPXP4PI","schema_version":"1.0","canonical_sha256":"b41f77f1e88ac488a9504ff0c506b4df882646de1c0b33079f947c3f07a45e9b","source":{"kind":"arxiv","id":"1711.01691","version":3},"attestation_state":"computed","paper":{"title":"Elastic LiDAR Fusion: Dense Map-Centric Continuous-Time SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Alberto Elfes, Chanoh Park, Clinton Fookes, Peyman Moghadam, Soohwan Kim, Sridha Sridharan","submitted_at":"2017-11-06T01:11:04Z","abstract_excerpt":"The concept of continuous-time trajectory representation has brought increased accuracy and efficiency to multi-modal sensor fusion in modern SLAM. However, regardless of these advantages, its offline property caused by the requirement of global batch optimization is critically hindering its relevance for real-time and life-long applications. In this paper, we present a dense map-centric SLAM method based on a continuous-time trajectory to cope with this problem. The proposed system locally functions in a similar fashion to conventional Continuous-Time SLAM (CT-SLAM). However, it removes the n"},"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":"1711.01691","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2017-11-06T01:11:04Z","cross_cats_sorted":[],"title_canon_sha256":"13dd5f8cf19dfd831b600152b67c9dcc57740e022b43c6926a8d6aecb69eaad1","abstract_canon_sha256":"fb3e75db4a49cd0c9de73a16b5c46504136a629640fc323dbb5e18b13bdddfd4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:02.714183Z","signature_b64":"Gr6DmcITBQX+rLFnKUXjVYm2dMYC/vccTYB3tkCsCsWuDnLJdf4iye0ehToNdkEhPEvJR5Z5w+UqjpHhTeD2Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b41f77f1e88ac488a9504ff0c506b4df882646de1c0b33079f947c3f07a45e9b","last_reissued_at":"2026-05-18T00:22:02.713693Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:02.713693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Elastic LiDAR Fusion: Dense Map-Centric Continuous-Time SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Alberto Elfes, Chanoh Park, Clinton Fookes, Peyman Moghadam, Soohwan Kim, Sridha Sridharan","submitted_at":"2017-11-06T01:11:04Z","abstract_excerpt":"The concept of continuous-time trajectory representation has brought increased accuracy and efficiency to multi-modal sensor fusion in modern SLAM. However, regardless of these advantages, its offline property caused by the requirement of global batch optimization is critically hindering its relevance for real-time and life-long applications. In this paper, we present a dense map-centric SLAM method based on a continuous-time trajectory to cope with this problem. The proposed system locally functions in a similar fashion to conventional Continuous-Time SLAM (CT-SLAM). However, it removes the n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.01691","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":""},"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":"1711.01691","created_at":"2026-05-18T00:22:02.713766+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.01691v3","created_at":"2026-05-18T00:22:02.713766+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.01691","created_at":"2026-05-18T00:22:02.713766+00:00"},{"alias_kind":"pith_short_12","alias_value":"WQPXP4PIRLCI","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_16","alias_value":"WQPXP4PIRLCIRKKQ","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_8","alias_value":"WQPXP4PI","created_at":"2026-05-18T12:31:53.515858+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/WQPXP4PIRLCIRKKQJ7YMKBVU36","json":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36.json","graph_json":"https://pith.science/api/pith-number/WQPXP4PIRLCIRKKQJ7YMKBVU36/graph.json","events_json":"https://pith.science/api/pith-number/WQPXP4PIRLCIRKKQJ7YMKBVU36/events.json","paper":"https://pith.science/paper/WQPXP4PI"},"agent_actions":{"view_html":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36","download_json":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36.json","view_paper":"https://pith.science/paper/WQPXP4PI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.01691&json=true","fetch_graph":"https://pith.science/api/pith-number/WQPXP4PIRLCIRKKQJ7YMKBVU36/graph.json","fetch_events":"https://pith.science/api/pith-number/WQPXP4PIRLCIRKKQJ7YMKBVU36/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36/action/storage_attestation","attest_author":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36/action/author_attestation","sign_citation":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36/action/citation_signature","submit_replication":"https://pith.science/pith/WQPXP4PIRLCIRKKQJ7YMKBVU36/action/replication_record"}},"created_at":"2026-05-18T00:22:02.713766+00:00","updated_at":"2026-05-18T00:22:02.713766+00:00"}