{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:DSZAOVO43DFH5XWBR6SX4POMZ4","short_pith_number":"pith:DSZAOVO4","schema_version":"1.0","canonical_sha256":"1cb20755dcd8ca7edec18fa57e3dcccf1217a06e387fff7e72dde33fb07527d3","source":{"kind":"arxiv","id":"2307.03355","version":2},"attestation_state":"computed","paper":{"title":"Optimized Path Planning for USVs under Ocean Currents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Behzad Akbari, Shiwei Liu, Tianye Wang, Ya-Jun Pan","submitted_at":"2023-07-07T02:28:51Z","abstract_excerpt":"Unmanned Surface Vehicles (USVs) in the ocean environment, considering various spatiotemporal factors such as ocean currents and other energy consumption factors. The paper uses Gaussian Process Motion Planning (GPMP2), a Bayesian optimization method that has shown promising results in continuous and nonlinear motion planning algorithms. The proposed work improves GPMP2 by incorporating a new spatiotemporal factor for tracking and predicting ocean currents using a spatiotemporal Bayesian inference. The algorithm is applied to the USV path planning and is shown to optimize for smoothness, obsta"},"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":"2307.03355","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-07-07T02:28:51Z","cross_cats_sorted":[],"title_canon_sha256":"1d662a5a9517c2499b586bdb1bffa7a0c2d8b0e5ef5d77437267b10d80b7ff1e","abstract_canon_sha256":"9a77df18e8f37c0f2a8bd9039590ef116bbc4a9f08a80ff3d2d91ac0154763ad"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:43:32.301997Z","signature_b64":"cOgbaQeJWNVyzVwWp055kzt3hvKAgOR+/Vhfgdq7kDDbfIPrDDvicWynECqih1+40dh9s/Jvpv0M1kB6YBVTDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1cb20755dcd8ca7edec18fa57e3dcccf1217a06e387fff7e72dde33fb07527d3","last_reissued_at":"2026-07-05T07:43:32.301558Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:43:32.301558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimized Path Planning for USVs under Ocean Currents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Behzad Akbari, Shiwei Liu, Tianye Wang, Ya-Jun Pan","submitted_at":"2023-07-07T02:28:51Z","abstract_excerpt":"Unmanned Surface Vehicles (USVs) in the ocean environment, considering various spatiotemporal factors such as ocean currents and other energy consumption factors. The paper uses Gaussian Process Motion Planning (GPMP2), a Bayesian optimization method that has shown promising results in continuous and nonlinear motion planning algorithms. The proposed work improves GPMP2 by incorporating a new spatiotemporal factor for tracking and predicting ocean currents using a spatiotemporal Bayesian inference. The algorithm is applied to the USV path planning and is shown to optimize for smoothness, obsta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.03355","kind":"arxiv","version":2},"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/2307.03355/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":"2307.03355","created_at":"2026-07-05T07:43:32.301611+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.03355v2","created_at":"2026-07-05T07:43:32.301611+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.03355","created_at":"2026-07-05T07:43:32.301611+00:00"},{"alias_kind":"pith_short_12","alias_value":"DSZAOVO43DFH","created_at":"2026-07-05T07:43:32.301611+00:00"},{"alias_kind":"pith_short_16","alias_value":"DSZAOVO43DFH5XWB","created_at":"2026-07-05T07:43:32.301611+00:00"},{"alias_kind":"pith_short_8","alias_value":"DSZAOVO4","created_at":"2026-07-05T07:43:32.301611+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/DSZAOVO43DFH5XWBR6SX4POMZ4","json":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4.json","graph_json":"https://pith.science/api/pith-number/DSZAOVO43DFH5XWBR6SX4POMZ4/graph.json","events_json":"https://pith.science/api/pith-number/DSZAOVO43DFH5XWBR6SX4POMZ4/events.json","paper":"https://pith.science/paper/DSZAOVO4"},"agent_actions":{"view_html":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4","download_json":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4.json","view_paper":"https://pith.science/paper/DSZAOVO4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.03355&json=true","fetch_graph":"https://pith.science/api/pith-number/DSZAOVO43DFH5XWBR6SX4POMZ4/graph.json","fetch_events":"https://pith.science/api/pith-number/DSZAOVO43DFH5XWBR6SX4POMZ4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4/action/storage_attestation","attest_author":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4/action/author_attestation","sign_citation":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4/action/citation_signature","submit_replication":"https://pith.science/pith/DSZAOVO43DFH5XWBR6SX4POMZ4/action/replication_record"}},"created_at":"2026-07-05T07:43:32.301611+00:00","updated_at":"2026-07-05T07:43:32.301611+00:00"}