{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:2SE6676WWSCSN6CMI6UEA7PXJO","short_pith_number":"pith:2SE6676W","schema_version":"1.0","canonical_sha256":"d489ef7fd6b48526f84c47a8407df74bbb829f1dd5cd794f18ade37994397bde","source":{"kind":"arxiv","id":"1710.02555","version":2},"attestation_state":"computed","paper":{"title":"Model Predictive Path-Following for Constrained Differentially Flat Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"cs.RO","authors_text":"Angela P. Schoellig, Melissa Greeff","submitted_at":"2017-10-06T18:56:13Z","abstract_excerpt":"For many tasks, predictive path-following control can significantly improve the performance and robustness of autonomous robots over traditional trajectory tracking control. It does this by prioritizing closeness to the path over timed progress along the path and by looking ahead to account for changes in the path. We propose a novel predictive path-following approach that couples feedforward linearization with path-based model predictive control. Our approach has a few key advantages. By utilizing the differential flatness property, we reduce the path-based model predictive control problem fr"},"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":"1710.02555","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2017-10-06T18:56:13Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"369310824e9d696a77f9ee47f22331517fb10f380e14d049de6408f8095127ef","abstract_canon_sha256":"c14bbfde6e16e50ff39fcac86439c7afe49ca3f998f63f67fc2b3da72686d13f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:30.693734Z","signature_b64":"j5v3sqkcTSDwPXgMZZS5cqykwm51BEO5V2/FPGErMaN70W1gxCEvn1lU06qsRpEyUWzwhfI8qynmGnttAWt6Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d489ef7fd6b48526f84c47a8407df74bbb829f1dd5cd794f18ade37994397bde","last_reissued_at":"2026-05-18T00:31:30.693027Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:30.693027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Model Predictive Path-Following for Constrained Differentially Flat Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"cs.RO","authors_text":"Angela P. Schoellig, Melissa Greeff","submitted_at":"2017-10-06T18:56:13Z","abstract_excerpt":"For many tasks, predictive path-following control can significantly improve the performance and robustness of autonomous robots over traditional trajectory tracking control. It does this by prioritizing closeness to the path over timed progress along the path and by looking ahead to account for changes in the path. We propose a novel predictive path-following approach that couples feedforward linearization with path-based model predictive control. Our approach has a few key advantages. By utilizing the differential flatness property, we reduce the path-based model predictive control problem fr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.02555","kind":"arxiv","version":2},"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":"1710.02555","created_at":"2026-05-18T00:31:30.693142+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.02555v2","created_at":"2026-05-18T00:31:30.693142+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.02555","created_at":"2026-05-18T00:31:30.693142+00:00"},{"alias_kind":"pith_short_12","alias_value":"2SE6676WWSCS","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"2SE6676WWSCSN6CM","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"2SE6676W","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/2SE6676WWSCSN6CMI6UEA7PXJO","json":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO.json","graph_json":"https://pith.science/api/pith-number/2SE6676WWSCSN6CMI6UEA7PXJO/graph.json","events_json":"https://pith.science/api/pith-number/2SE6676WWSCSN6CMI6UEA7PXJO/events.json","paper":"https://pith.science/paper/2SE6676W"},"agent_actions":{"view_html":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO","download_json":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO.json","view_paper":"https://pith.science/paper/2SE6676W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.02555&json=true","fetch_graph":"https://pith.science/api/pith-number/2SE6676WWSCSN6CMI6UEA7PXJO/graph.json","fetch_events":"https://pith.science/api/pith-number/2SE6676WWSCSN6CMI6UEA7PXJO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO/action/storage_attestation","attest_author":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO/action/author_attestation","sign_citation":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO/action/citation_signature","submit_replication":"https://pith.science/pith/2SE6676WWSCSN6CMI6UEA7PXJO/action/replication_record"}},"created_at":"2026-05-18T00:31:30.693142+00:00","updated_at":"2026-05-18T00:31:30.693142+00:00"}