{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2EN43MZVYQXUBURXOP4QRCHOAE","short_pith_number":"pith:2EN43MZV","schema_version":"1.0","canonical_sha256":"d11bcdb335c42f40d23773f90888ee013fdb952231896b5def5a5c8ff88c8f8e","source":{"kind":"arxiv","id":"1711.04040","version":1},"attestation_state":"computed","paper":{"title":"Anytime Motion Planning on Large Dense Roadmaps with Expensive Edge Evaluations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Christopher M. Dellin, Oren Salzman, Sanjiban Choudhury, Shushman Choudhury, Siddhartha S. Srinivasa","submitted_at":"2017-11-10T23:05:59Z","abstract_excerpt":"We propose an algorithmic framework for efficient anytime motion planning on large dense geometric roadmaps, in domains where collision checks and therefore edge evaluations are computationally expensive. A large dense roadmap (graph) can typically ensure the existence of high quality solutions for most motion-planning problems, but the size of the roadmap, particularly in high-dimensional spaces, makes existing search-based planning algorithms computationally expensive. We deal with the challenges of expensive search and collision checking in two ways. First, we frame the problem of anytime m"},"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":"1711.04040","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2017-11-10T23:05:59Z","cross_cats_sorted":[],"title_canon_sha256":"2132fb0c96e50cdd78ff9ab912927118bc27628759586507c7bb8d60ef9955d0","abstract_canon_sha256":"d5777a26c515a89cd60eb967ef8abf7281835cb72818763e51833b56cb2725fd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:50.261821Z","signature_b64":"sjXnXobrfrrWNbCwnaE6yOco1xe/AUcKiG/GNgwsk57ZEfHTmj0xgf6wRx/K06J5QZ5/r4S/W4DkAjpot2CMAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d11bcdb335c42f40d23773f90888ee013fdb952231896b5def5a5c8ff88c8f8e","last_reissued_at":"2026-05-18T00:30:50.261160Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:50.261160Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Anytime Motion Planning on Large Dense Roadmaps with Expensive Edge Evaluations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Christopher M. Dellin, Oren Salzman, Sanjiban Choudhury, Shushman Choudhury, Siddhartha S. Srinivasa","submitted_at":"2017-11-10T23:05:59Z","abstract_excerpt":"We propose an algorithmic framework for efficient anytime motion planning on large dense geometric roadmaps, in domains where collision checks and therefore edge evaluations are computationally expensive. A large dense roadmap (graph) can typically ensure the existence of high quality solutions for most motion-planning problems, but the size of the roadmap, particularly in high-dimensional spaces, makes existing search-based planning algorithms computationally expensive. We deal with the challenges of expensive search and collision checking in two ways. First, we frame the problem of anytime m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.04040","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":"1711.04040","created_at":"2026-05-18T00:30:50.261267+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.04040v1","created_at":"2026-05-18T00:30:50.261267+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.04040","created_at":"2026-05-18T00:30:50.261267+00:00"},{"alias_kind":"pith_short_12","alias_value":"2EN43MZVYQXU","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2EN43MZVYQXUBURX","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2EN43MZV","created_at":"2026-05-18T12:30:55.937587+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/2EN43MZVYQXUBURXOP4QRCHOAE","json":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE.json","graph_json":"https://pith.science/api/pith-number/2EN43MZVYQXUBURXOP4QRCHOAE/graph.json","events_json":"https://pith.science/api/pith-number/2EN43MZVYQXUBURXOP4QRCHOAE/events.json","paper":"https://pith.science/paper/2EN43MZV"},"agent_actions":{"view_html":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE","download_json":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE.json","view_paper":"https://pith.science/paper/2EN43MZV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.04040&json=true","fetch_graph":"https://pith.science/api/pith-number/2EN43MZVYQXUBURXOP4QRCHOAE/graph.json","fetch_events":"https://pith.science/api/pith-number/2EN43MZVYQXUBURXOP4QRCHOAE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE/action/storage_attestation","attest_author":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE/action/author_attestation","sign_citation":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE/action/citation_signature","submit_replication":"https://pith.science/pith/2EN43MZVYQXUBURXOP4QRCHOAE/action/replication_record"}},"created_at":"2026-05-18T00:30:50.261267+00:00","updated_at":"2026-05-18T00:30:50.261267+00:00"}