{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:Y5CCTJ2JWJHOQHQ6ZRFPIABNRH","short_pith_number":"pith:Y5CCTJ2J","schema_version":"1.0","canonical_sha256":"c74429a749b24ee81e1ecc4af4002d89d8c5a1997226abaa07209b2b6a07806a","source":{"kind":"arxiv","id":"1808.06820","version":1},"attestation_state":"computed","paper":{"title":"SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Andrew J Davison, Andy Nisbet, Bruno Bodin, Emanuele Vespa, Harry Wagstaff, John H Mayer, Luigi Nardi, Michael O'Boyle, Mikel Luj\\'an, Paul H.J. Kelly, Sajad Saeedi, Steve Furber","submitted_at":"2018-08-21T09:49:51Z","abstract_excerpt":"SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify the interface of such algorithms, or to perform a holistic comparison of their capabilities. This is a problem since different SLAM applications can have different functional and non-functional requirements. For example, a mobile phonebased AR application has a tight energy budget, while a UAV navigation system usually requires high accuracy. SLAMBench2 is a benchmarking framework to evaluate existing and future SLAM"},"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":"1808.06820","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-08-21T09:49:51Z","cross_cats_sorted":[],"title_canon_sha256":"3f955c85a894a48d1ce5aa0ab5bd6bd021556cc809afe1cb05d9041114626824","abstract_canon_sha256":"1f61f1b5d79b63ff4291172e28d61fdb01d58030f1206dc0eccf40bc83852919"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:38.970749Z","signature_b64":"tQDxP5/43q9EdL/IOHpU/I5z3aZ6aghMJUVia5pGL5hCbVLbKTGJdU/Bz1lGSPVEcuo9suXscqMOcUzPV3mSAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c74429a749b24ee81e1ecc4af4002d89d8c5a1997226abaa07209b2b6a07806a","last_reissued_at":"2026-05-18T00:07:38.970022Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:38.970022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Andrew J Davison, Andy Nisbet, Bruno Bodin, Emanuele Vespa, Harry Wagstaff, John H Mayer, Luigi Nardi, Michael O'Boyle, Mikel Luj\\'an, Paul H.J. Kelly, Sajad Saeedi, Steve Furber","submitted_at":"2018-08-21T09:49:51Z","abstract_excerpt":"SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify the interface of such algorithms, or to perform a holistic comparison of their capabilities. This is a problem since different SLAM applications can have different functional and non-functional requirements. For example, a mobile phonebased AR application has a tight energy budget, while a UAV navigation system usually requires high accuracy. SLAMBench2 is a benchmarking framework to evaluate existing and future SLAM"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.06820","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":"1808.06820","created_at":"2026-05-18T00:07:38.970147+00:00"},{"alias_kind":"arxiv_version","alias_value":"1808.06820v1","created_at":"2026-05-18T00:07:38.970147+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.06820","created_at":"2026-05-18T00:07:38.970147+00:00"},{"alias_kind":"pith_short_12","alias_value":"Y5CCTJ2JWJHO","created_at":"2026-05-18T12:33:04.347982+00:00"},{"alias_kind":"pith_short_16","alias_value":"Y5CCTJ2JWJHOQHQ6","created_at":"2026-05-18T12:33:04.347982+00:00"},{"alias_kind":"pith_short_8","alias_value":"Y5CCTJ2J","created_at":"2026-05-18T12:33:04.347982+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/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH","json":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH.json","graph_json":"https://pith.science/api/pith-number/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/graph.json","events_json":"https://pith.science/api/pith-number/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/events.json","paper":"https://pith.science/paper/Y5CCTJ2J"},"agent_actions":{"view_html":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH","download_json":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH.json","view_paper":"https://pith.science/paper/Y5CCTJ2J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1808.06820&json=true","fetch_graph":"https://pith.science/api/pith-number/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/graph.json","fetch_events":"https://pith.science/api/pith-number/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/action/storage_attestation","attest_author":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/action/author_attestation","sign_citation":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/action/citation_signature","submit_replication":"https://pith.science/pith/Y5CCTJ2JWJHOQHQ6ZRFPIABNRH/action/replication_record"}},"created_at":"2026-05-18T00:07:38.970147+00:00","updated_at":"2026-05-18T00:07:38.970147+00:00"}