{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZBWAPWGANVXB2VRQEVJYW3OQUV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f0efe48e5e5a43648efd57e101cb6b93a7902504abb0e8577969d9c3a6f583f7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2025-06-10T04:16:10Z","title_canon_sha256":"08becee16c8b0803c8a8b652ff2bf4c6bc2388daa4306cb61e9ffce104a08bd9"},"schema_version":"1.0","source":{"id":"2506.08434","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.08434","created_at":"2026-07-05T11:18:49Z"},{"alias_kind":"arxiv_version","alias_value":"2506.08434v1","created_at":"2026-07-05T11:18:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.08434","created_at":"2026-07-05T11:18:49Z"},{"alias_kind":"pith_short_12","alias_value":"ZBWAPWGANVXB","created_at":"2026-07-05T11:18:49Z"},{"alias_kind":"pith_short_16","alias_value":"ZBWAPWGANVXB2VRQ","created_at":"2026-07-05T11:18:49Z"},{"alias_kind":"pith_short_8","alias_value":"ZBWAPWGA","created_at":"2026-07-05T11:18:49Z"}],"graph_snapshots":[{"event_id":"sha256:9da60eab9cba23b440ffa73bdeba97e9e874323f3105525ae80c8b9610376b0f","target":"graph","created_at":"2026-07-05T11:18:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2506.08434/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we propose an attention-based deep reinforcement learning approach to address the adaptive informative path planning (IPP) problem in 3D space, where an aerial robot equipped with a downward-facing sensor must dynamically adjust its 3D position to balance sensing footprint and accuracy, and finally obtain a high-quality belief of an underlying field of interest over a given domain (e.g., presence of specific plants, hazardous gas, geological structures, etc.). In adaptive IPP tasks, the agent is tasked with maximizing information collected under time/distance constraints, continu","authors_text":"Guillaume Sartoretti, Rui Zhao, Xingjian Zhang, Yizhuo Wang, Yuhong Cao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2025-06-10T04:16:10Z","title":"Attention-based Learning for 3D Informative Path Planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.08434","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7c412fef5a8363d1b7a8603dd39ccf666c405a0fa11d339ac59549e8f8527fab","target":"record","created_at":"2026-07-05T11:18:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f0efe48e5e5a43648efd57e101cb6b93a7902504abb0e8577969d9c3a6f583f7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2025-06-10T04:16:10Z","title_canon_sha256":"08becee16c8b0803c8a8b652ff2bf4c6bc2388daa4306cb61e9ffce104a08bd9"},"schema_version":"1.0","source":{"id":"2506.08434","kind":"arxiv","version":1}},"canonical_sha256":"c86c07d8c06d6e1d563025538b6dd0a572b25cd1656ad28ce666fec1d35f8ecb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c86c07d8c06d6e1d563025538b6dd0a572b25cd1656ad28ce666fec1d35f8ecb","first_computed_at":"2026-07-05T11:18:49.424545Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:18:49.424545Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KbAiKHn7EIRcYVAuRgNqWMpkv8YW9keGbAsdTVO4/DLgRVTlr/tag5bnYnBtmCIeiSZrHQY4Cs30v7fLXx7XBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:18:49.425020Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.08434","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c412fef5a8363d1b7a8603dd39ccf666c405a0fa11d339ac59549e8f8527fab","sha256:9da60eab9cba23b440ffa73bdeba97e9e874323f3105525ae80c8b9610376b0f"],"state_sha256":"f9275937bec991267d7c5facb6ee7bc26553170f37cf59860bfde807ce3deefc"}