{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:M6AMBJVYTNRIDP3HG3KJB6ELGB","short_pith_number":"pith:M6AMBJVY","schema_version":"1.0","canonical_sha256":"6780c0a6b89b6281bf6736d490f88b306f57e66c03cd534ae6a8a0f7ea16d9f5","source":{"kind":"arxiv","id":"2504.15138","version":1},"attestation_state":"computed","paper":{"title":"Automatic Generation of Aerobatic Flight in Complex Environments via Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Anke Zhao, Fei Gao, Tianyue Wu, Tingrui Zhang, Yuhang Zhong","submitted_at":"2025-04-21T14:40:55Z","abstract_excerpt":"Performing striking aerobatic flight in complex environments demands manual designs of key maneuvers in advance, which is intricate and time-consuming as the horizon of the trajectory performed becomes long. This paper presents a novel framework that leverages diffusion models to automate and scale up aerobatic trajectory generation. Our key innovation is the decomposition of complex maneuvers into aerobatic primitives, which are short frame sequences that act as building blocks, featuring critical aerobatic behaviors for tractable trajectory synthesis. The model learns aerobatic primitives us"},"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":"2504.15138","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-04-21T14:40:55Z","cross_cats_sorted":[],"title_canon_sha256":"43652bfd815eb863a660713b3c6095b0d9514c3bb298608ab77a967bdd00a63f","abstract_canon_sha256":"1f118aa519ee0e407adce9e8340c1ae7efcb7fd9d42e3e758ae22dfb3fe4f7cd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:51:56.691231Z","signature_b64":"RAQ5IGiEvOdCqIp/q/hSXdR+WsMNJ5MEtTCTA3691eyQrKv3UCVT+beJLLwks6b88kioXA2hhcbO/msP8ZjuAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6780c0a6b89b6281bf6736d490f88b306f57e66c03cd534ae6a8a0f7ea16d9f5","last_reissued_at":"2026-07-05T10:51:56.690824Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:51:56.690824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automatic Generation of Aerobatic Flight in Complex Environments via Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Anke Zhao, Fei Gao, Tianyue Wu, Tingrui Zhang, Yuhang Zhong","submitted_at":"2025-04-21T14:40:55Z","abstract_excerpt":"Performing striking aerobatic flight in complex environments demands manual designs of key maneuvers in advance, which is intricate and time-consuming as the horizon of the trajectory performed becomes long. This paper presents a novel framework that leverages diffusion models to automate and scale up aerobatic trajectory generation. Our key innovation is the decomposition of complex maneuvers into aerobatic primitives, which are short frame sequences that act as building blocks, featuring critical aerobatic behaviors for tractable trajectory synthesis. The model learns aerobatic primitives us"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.15138","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/2504.15138/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":"2504.15138","created_at":"2026-07-05T10:51:56.690881+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.15138v1","created_at":"2026-07-05T10:51:56.690881+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.15138","created_at":"2026-07-05T10:51:56.690881+00:00"},{"alias_kind":"pith_short_12","alias_value":"M6AMBJVYTNRI","created_at":"2026-07-05T10:51:56.690881+00:00"},{"alias_kind":"pith_short_16","alias_value":"M6AMBJVYTNRIDP3H","created_at":"2026-07-05T10:51:56.690881+00:00"},{"alias_kind":"pith_short_8","alias_value":"M6AMBJVY","created_at":"2026-07-05T10:51:56.690881+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/M6AMBJVYTNRIDP3HG3KJB6ELGB","json":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB.json","graph_json":"https://pith.science/api/pith-number/M6AMBJVYTNRIDP3HG3KJB6ELGB/graph.json","events_json":"https://pith.science/api/pith-number/M6AMBJVYTNRIDP3HG3KJB6ELGB/events.json","paper":"https://pith.science/paper/M6AMBJVY"},"agent_actions":{"view_html":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB","download_json":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB.json","view_paper":"https://pith.science/paper/M6AMBJVY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.15138&json=true","fetch_graph":"https://pith.science/api/pith-number/M6AMBJVYTNRIDP3HG3KJB6ELGB/graph.json","fetch_events":"https://pith.science/api/pith-number/M6AMBJVYTNRIDP3HG3KJB6ELGB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB/action/storage_attestation","attest_author":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB/action/author_attestation","sign_citation":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB/action/citation_signature","submit_replication":"https://pith.science/pith/M6AMBJVYTNRIDP3HG3KJB6ELGB/action/replication_record"}},"created_at":"2026-07-05T10:51:56.690881+00:00","updated_at":"2026-07-05T10:51:56.690881+00:00"}