{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ZZENL37JRHRSQWS7NLMORRTLBC","short_pith_number":"pith:ZZENL37J","schema_version":"1.0","canonical_sha256":"ce48d5efe989e3285a5f6ad8e8c66b08a7b9cdc8f54dfadec3984b7977556b2a","source":{"kind":"arxiv","id":"2407.13543","version":1},"attestation_state":"computed","paper":{"title":"Scalar Field Mapping with Adaptive High-Intensity Region Avoidance","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Muzaffar Qureshi, Rushikesh Kamalapurkar, Tochukwu Elijah Ogri, Zachary I. Bell","submitted_at":"2024-07-18T14:18:31Z","abstract_excerpt":"This research is motivated by a scenario where a group of UAVs is assigned to map an unknown scalar field, with the imperative of maintaining a safe distance from the sources of the field to evade detection or damage. The location of the sources is unknown a priori, so the UAVs rely on measurements of the field intensity to gauge safety. The UAVs estimate the unknown scalar field using Gaussian process (GP) regression and use the estimate to generate a map of high-intensity regions using Hough transform (HT), updated online based on the field measurements. A convergence analysis shows the boun"},"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":"2407.13543","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2024-07-18T14:18:31Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"db39150f2cd756f6919900b21da69b923df4b1fe94bdf6e64c29a0f266379a13","abstract_canon_sha256":"8557b2d17f659e0649e3e648188065e4e0480ce825f4a12c26e75addee1bdf4b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:34:16.673604Z","signature_b64":"0Q1QtqpSp4qSVyJ4FROVA/ONPKuCjC7Fb8WMRb/UmeLJ7+CetDpAa6emd2CTESdVUcOKZgA3numeADG9HgvWAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce48d5efe989e3285a5f6ad8e8c66b08a7b9cdc8f54dfadec3984b7977556b2a","last_reissued_at":"2026-07-05T09:34:16.673105Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:34:16.673105Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scalar Field Mapping with Adaptive High-Intensity Region Avoidance","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Muzaffar Qureshi, Rushikesh Kamalapurkar, Tochukwu Elijah Ogri, Zachary I. Bell","submitted_at":"2024-07-18T14:18:31Z","abstract_excerpt":"This research is motivated by a scenario where a group of UAVs is assigned to map an unknown scalar field, with the imperative of maintaining a safe distance from the sources of the field to evade detection or damage. The location of the sources is unknown a priori, so the UAVs rely on measurements of the field intensity to gauge safety. The UAVs estimate the unknown scalar field using Gaussian process (GP) regression and use the estimate to generate a map of high-intensity regions using Hough transform (HT), updated online based on the field measurements. A convergence analysis shows the boun"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.13543","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/2407.13543/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":"2407.13543","created_at":"2026-07-05T09:34:16.673160+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.13543v1","created_at":"2026-07-05T09:34:16.673160+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.13543","created_at":"2026-07-05T09:34:16.673160+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZZENL37JRHRS","created_at":"2026-07-05T09:34:16.673160+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZZENL37JRHRSQWS7","created_at":"2026-07-05T09:34:16.673160+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZZENL37J","created_at":"2026-07-05T09:34:16.673160+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/ZZENL37JRHRSQWS7NLMORRTLBC","json":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC.json","graph_json":"https://pith.science/api/pith-number/ZZENL37JRHRSQWS7NLMORRTLBC/graph.json","events_json":"https://pith.science/api/pith-number/ZZENL37JRHRSQWS7NLMORRTLBC/events.json","paper":"https://pith.science/paper/ZZENL37J"},"agent_actions":{"view_html":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC","download_json":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC.json","view_paper":"https://pith.science/paper/ZZENL37J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.13543&json=true","fetch_graph":"https://pith.science/api/pith-number/ZZENL37JRHRSQWS7NLMORRTLBC/graph.json","fetch_events":"https://pith.science/api/pith-number/ZZENL37JRHRSQWS7NLMORRTLBC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC/action/storage_attestation","attest_author":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC/action/author_attestation","sign_citation":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC/action/citation_signature","submit_replication":"https://pith.science/pith/ZZENL37JRHRSQWS7NLMORRTLBC/action/replication_record"}},"created_at":"2026-07-05T09:34:16.673160+00:00","updated_at":"2026-07-05T09:34:16.673160+00:00"}