{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:D47RKGKTMNAYR7JONRATNJZ273","short_pith_number":"pith:D47RKGKT","schema_version":"1.0","canonical_sha256":"1f3f151953634188fd2e6c4136a73afecb9d0620b67c1d254dda8d20ad8f07e4","source":{"kind":"arxiv","id":"1907.07647","version":1},"attestation_state":"computed","paper":{"title":"Fly Safe: Aerial Swarm Robotics using Force Field Particle Swarm Optimisation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"James Butterworth, Lauren Parker, Shan Luo","submitted_at":"2019-07-17T17:11:13Z","abstract_excerpt":"Particle Swarm Optimisation (PSO) is a powerful optimisation algorithm that can be used to locate global maxima in a search space. Recent interest in swarms of Micro Aerial Vehicles (MAVs) begs the question as to whether PSO can be used as a method to enable real robotic swarms to locate a target goal point. However, the original PSO algorithm does not take into account collisions between particles during search. In this paper we propose a novel algorithm called Force Field Particle Swarm Optimisation (FFPSO) that designates repellent force fields to particles such that these fields provide an"},"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":"1907.07647","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-07-17T17:11:13Z","cross_cats_sorted":[],"title_canon_sha256":"31ecb3adef99577f2e5a2588860822c97fb8ba64ee15dac0de2547bb8e4b8b3a","abstract_canon_sha256":"612fef6cf47ac2c58b754c867641f7f9d7050502b968681ba00c17f28748b709"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:21.437794Z","signature_b64":"D1LE2UwKrQhzyyf69daNRRQnJIufJU84X0Oy1E+/fJGjmUETzyhll8InOtix3ts701gXdIY3o7cf9AdPY0cLAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f3f151953634188fd2e6c4136a73afecb9d0620b67c1d254dda8d20ad8f07e4","last_reissued_at":"2026-05-17T23:40:21.437082Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:21.437082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fly Safe: Aerial Swarm Robotics using Force Field Particle Swarm Optimisation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"James Butterworth, Lauren Parker, Shan Luo","submitted_at":"2019-07-17T17:11:13Z","abstract_excerpt":"Particle Swarm Optimisation (PSO) is a powerful optimisation algorithm that can be used to locate global maxima in a search space. Recent interest in swarms of Micro Aerial Vehicles (MAVs) begs the question as to whether PSO can be used as a method to enable real robotic swarms to locate a target goal point. However, the original PSO algorithm does not take into account collisions between particles during search. In this paper we propose a novel algorithm called Force Field Particle Swarm Optimisation (FFPSO) that designates repellent force fields to particles such that these fields provide an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07647","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":"1907.07647","created_at":"2026-05-17T23:40:21.437191+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.07647v1","created_at":"2026-05-17T23:40:21.437191+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07647","created_at":"2026-05-17T23:40:21.437191+00:00"},{"alias_kind":"pith_short_12","alias_value":"D47RKGKTMNAY","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"D47RKGKTMNAYR7JO","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"D47RKGKT","created_at":"2026-05-18T12:33:15.570797+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/D47RKGKTMNAYR7JONRATNJZ273","json":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273.json","graph_json":"https://pith.science/api/pith-number/D47RKGKTMNAYR7JONRATNJZ273/graph.json","events_json":"https://pith.science/api/pith-number/D47RKGKTMNAYR7JONRATNJZ273/events.json","paper":"https://pith.science/paper/D47RKGKT"},"agent_actions":{"view_html":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273","download_json":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273.json","view_paper":"https://pith.science/paper/D47RKGKT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.07647&json=true","fetch_graph":"https://pith.science/api/pith-number/D47RKGKTMNAYR7JONRATNJZ273/graph.json","fetch_events":"https://pith.science/api/pith-number/D47RKGKTMNAYR7JONRATNJZ273/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273/action/timestamp_anchor","attest_storage":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273/action/storage_attestation","attest_author":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273/action/author_attestation","sign_citation":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273/action/citation_signature","submit_replication":"https://pith.science/pith/D47RKGKTMNAYR7JONRATNJZ273/action/replication_record"}},"created_at":"2026-05-17T23:40:21.437191+00:00","updated_at":"2026-05-17T23:40:21.437191+00:00"}