{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:O4Q2PZLIN3KVES357EWUISHD5R","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":"d3283c74ffbf76ac5f5a47917f8c274e35aad875bcb3842ab8f38b9d38dd37a5","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-09-02T20:28:28Z","title_canon_sha256":"b1bb39b9f31922a415fafa31ccb1eff530d60afb274d2a7f6ce9a3ad333a8440"},"schema_version":"1.0","source":{"id":"1709.00627","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.00627","created_at":"2026-05-18T00:15:37Z"},{"alias_kind":"arxiv_version","alias_value":"1709.00627v3","created_at":"2026-05-18T00:15:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.00627","created_at":"2026-05-18T00:15:37Z"},{"alias_kind":"pith_short_12","alias_value":"O4Q2PZLIN3KV","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"O4Q2PZLIN3KVES35","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"O4Q2PZLI","created_at":"2026-05-18T12:31:34Z"}],"graph_snapshots":[{"event_id":"sha256:d80e6e7439c8f605ab2d922e6e902b7b8da8e5c40dd435627db4ca2143b41ff5","target":"graph","created_at":"2026-05-18T00:15:37Z","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"},"paper":{"abstract_excerpt":"With the development of robotics, there are growing needs for real time motion planning. However, due to obstacles in the environment, the planning problem is highly non-convex, which makes it difficult to achieve real time computation using existing non-convex optimization algorithms. This paper introduces the convex feasible set algorithm (CFS) which is a fast algorithm for non-convex optimization problems that have convex costs and non-convex constraints. The idea is to find a convex feasible set for the original problem and iteratively solve a sequence of subproblems using the convex const","authors_text":"Changliu Liu, Chung-Yen Lin, Masayoshi Tomizuka","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-09-02T20:28:28Z","title":"The Convex Feasible Set Algorithm for Real Time Optimization in Motion Planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.00627","kind":"arxiv","version":3},"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:a2ac410bdf6dc69398697c9e7105ceb0e21aeb22f1e683576554ec9d877b492a","target":"record","created_at":"2026-05-18T00:15:37Z","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":"d3283c74ffbf76ac5f5a47917f8c274e35aad875bcb3842ab8f38b9d38dd37a5","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-09-02T20:28:28Z","title_canon_sha256":"b1bb39b9f31922a415fafa31ccb1eff530d60afb274d2a7f6ce9a3ad333a8440"},"schema_version":"1.0","source":{"id":"1709.00627","kind":"arxiv","version":3}},"canonical_sha256":"7721a7e5686ed5524b7df92d4448e3ec5630427ca1a090077a81f7644d57363d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7721a7e5686ed5524b7df92d4448e3ec5630427ca1a090077a81f7644d57363d","first_computed_at":"2026-05-18T00:15:37.425242Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:37.425242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nDy8v92YRyitMwglF4AxJRaJOOvZSJq8P2VPu/Hz4daM9HInnrKi2q8wO1cgzLJzMthxCzQAlyBFaHZIM9I7DA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:37.425698Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.00627","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2ac410bdf6dc69398697c9e7105ceb0e21aeb22f1e683576554ec9d877b492a","sha256:d80e6e7439c8f605ab2d922e6e902b7b8da8e5c40dd435627db4ca2143b41ff5"],"state_sha256":"2d893167654816b8a0fb99a4ddbb46ea0085faac1ccfc1a8ac31f319129bd36d"}