{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:QKCKKX5VCEYXQAVZFN4TMVJSYG","short_pith_number":"pith:QKCKKX5V","schema_version":"1.0","canonical_sha256":"8284a55fb511317802b92b79365532c1812efb329bf5965e5c265a1adf60d752","source":{"kind":"arxiv","id":"2412.00291","version":1},"attestation_state":"computed","paper":{"title":"Real-Time Metric-Semantic Mapping for Autonomous Navigation in Outdoor Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Bowen Yang, Dimitrios Kanoulas, Jianhao Jiao, Jin Wu, Lujia Wang, Ming Liu, Ren Xin, Rui Fan, Ruoyu Geng, Yuanhang Li","submitted_at":"2024-11-30T00:05:10Z","abstract_excerpt":"The creation of a metric-semantic map, which encodes human-prior knowledge, represents a high-level abstraction of environments. However, constructing such a map poses challenges related to the fusion of multi-modal sensor data, the attainment of real-time mapping performance, and the preservation of structural and semantic information consistency. In this paper, we introduce an online metric-semantic mapping system that utilizes LiDAR-Visual-Inertial sensing to generate a global metric-semantic mesh map of large-scale outdoor environments. Leveraging GPU acceleration, our mapping process achi"},"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":"2412.00291","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-30T00:05:10Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"0afce70f3e355cd30e844d315632d70cd979951bee8279f92ab841f9dd207317","abstract_canon_sha256":"088c241bb3ed78ac9fc4919234497f1e6706184e316594a468275ad4c56e6417"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:42:39.016650Z","signature_b64":"Zn34o/ffW5w+nBOa/6I1H1teo92rM0nI/GYIcgV/2m+kSmyFj8Sespicprx1favpRIBKmwkEU0PYmH0sNZ7bAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8284a55fb511317802b92b79365532c1812efb329bf5965e5c265a1adf60d752","last_reissued_at":"2026-07-05T09:42:39.016249Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:42:39.016249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Real-Time Metric-Semantic Mapping for Autonomous Navigation in Outdoor Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Bowen Yang, Dimitrios Kanoulas, Jianhao Jiao, Jin Wu, Lujia Wang, Ming Liu, Ren Xin, Rui Fan, Ruoyu Geng, Yuanhang Li","submitted_at":"2024-11-30T00:05:10Z","abstract_excerpt":"The creation of a metric-semantic map, which encodes human-prior knowledge, represents a high-level abstraction of environments. However, constructing such a map poses challenges related to the fusion of multi-modal sensor data, the attainment of real-time mapping performance, and the preservation of structural and semantic information consistency. In this paper, we introduce an online metric-semantic mapping system that utilizes LiDAR-Visual-Inertial sensing to generate a global metric-semantic mesh map of large-scale outdoor environments. Leveraging GPU acceleration, our mapping process achi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00291","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.00291/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":"2412.00291","created_at":"2026-07-05T09:42:39.016305+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.00291v1","created_at":"2026-07-05T09:42:39.016305+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00291","created_at":"2026-07-05T09:42:39.016305+00:00"},{"alias_kind":"pith_short_12","alias_value":"QKCKKX5VCEYX","created_at":"2026-07-05T09:42:39.016305+00:00"},{"alias_kind":"pith_short_16","alias_value":"QKCKKX5VCEYXQAVZ","created_at":"2026-07-05T09:42:39.016305+00:00"},{"alias_kind":"pith_short_8","alias_value":"QKCKKX5V","created_at":"2026-07-05T09:42:39.016305+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/QKCKKX5VCEYXQAVZFN4TMVJSYG","json":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG.json","graph_json":"https://pith.science/api/pith-number/QKCKKX5VCEYXQAVZFN4TMVJSYG/graph.json","events_json":"https://pith.science/api/pith-number/QKCKKX5VCEYXQAVZFN4TMVJSYG/events.json","paper":"https://pith.science/paper/QKCKKX5V"},"agent_actions":{"view_html":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG","download_json":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG.json","view_paper":"https://pith.science/paper/QKCKKX5V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.00291&json=true","fetch_graph":"https://pith.science/api/pith-number/QKCKKX5VCEYXQAVZFN4TMVJSYG/graph.json","fetch_events":"https://pith.science/api/pith-number/QKCKKX5VCEYXQAVZFN4TMVJSYG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG/action/storage_attestation","attest_author":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG/action/author_attestation","sign_citation":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG/action/citation_signature","submit_replication":"https://pith.science/pith/QKCKKX5VCEYXQAVZFN4TMVJSYG/action/replication_record"}},"created_at":"2026-07-05T09:42:39.016305+00:00","updated_at":"2026-07-05T09:42:39.016305+00:00"}