{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:Z2PIALJXKCI6UZVDDYVDWKCUUY","short_pith_number":"pith:Z2PIALJX","canonical_record":{"source":{"id":"2403.01830","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-04T08:26:14Z","cross_cats_sorted":["cs.SY","math.OC"],"title_canon_sha256":"b07957ac130b41fde7fd20f317d6988179cc27c3c42d61fbd43d3bc5fab46b2d","abstract_canon_sha256":"0f98330fbc80e400d9ceae5ff6806ed7c0926b6aafa29cff5cec6b5fd7cef7a9"},"schema_version":"1.0"},"canonical_sha256":"ce9e802d375091ea66a31e2a3b2854a61382e482152f9a1702f8b2f155cad0a7","source":{"kind":"arxiv","id":"2403.01830","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.01830","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"arxiv_version","alias_value":"2403.01830v1","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.01830","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"pith_short_12","alias_value":"Z2PIALJXKCI6","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"pith_short_16","alias_value":"Z2PIALJXKCI6UZVD","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"pith_short_8","alias_value":"Z2PIALJX","created_at":"2026-07-05T07:51:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:Z2PIALJXKCI6UZVDDYVDWKCUUY","target":"record","payload":{"canonical_record":{"source":{"id":"2403.01830","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-04T08:26:14Z","cross_cats_sorted":["cs.SY","math.OC"],"title_canon_sha256":"b07957ac130b41fde7fd20f317d6988179cc27c3c42d61fbd43d3bc5fab46b2d","abstract_canon_sha256":"0f98330fbc80e400d9ceae5ff6806ed7c0926b6aafa29cff5cec6b5fd7cef7a9"},"schema_version":"1.0"},"canonical_sha256":"ce9e802d375091ea66a31e2a3b2854a61382e482152f9a1702f8b2f155cad0a7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:51:52.541972Z","signature_b64":"qJZJ5RxvRRn+cm3u7/IUPx7o+CxBpTxcXASgrZx6T5f7e2R4xHlCLrB/9vlyjSdDz58SlSmNajyCwImJ2L0CDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce9e802d375091ea66a31e2a3b2854a61382e482152f9a1702f8b2f155cad0a7","last_reissued_at":"2026-07-05T07:51:52.541541Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:51:52.541541Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.01830","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:51:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tYhgvK25/JlqsBUxBIwq0b7B4CRo1hWfNZ+QpGGb4VBL8BNLfCyPWyvLyeLM2nAz5b0JniAFyeMbC2d0DTYZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T08:05:21.908404Z"},"content_sha256":"5a931b0fa7aa6bdaf7f64ed19c3de617cd0d73144e0aaf69dd7138677d8da08b","schema_version":"1.0","event_id":"sha256:5a931b0fa7aa6bdaf7f64ed19c3de617cd0d73144e0aaf69dd7138677d8da08b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:Z2PIALJXKCI6UZVDDYVDWKCUUY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Progressive Smoothing for Motion Planning in Real-Time NMPC","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.SY","math.OC"],"primary_cat":"eess.SY","authors_text":"Katrin Baumg\\\"artner, Moritz Diehl, Rien Quirynen, Rudolf Reiter","submitted_at":"2024-03-04T08:26:14Z","abstract_excerpt":"Nonlinear model predictive control (NMPC) is a popular strategy for solving motion planning problems, including obstacle avoidance constraints, in autonomous driving applications. Non-smooth obstacle shapes, such as rectangles, introduce additional local minima in the underlying optimization problem. Smooth over-approximations, e.g., ellipsoidal shapes, limit the performance due to their conservativeness. We propose to vary the smoothness and the related over-approximation by a homotopy. Instead of varying the smoothness in consecutive sequential quadratic programming iterations, we use formul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.01830","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/2403.01830/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:51:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OSbhHjhUTWtw3keE1xs1AHUJkXOyVgtK8NCFix4G9qNKMe00G2k/iK+S02iyaAFrU0azUYN/UGiWlYWBT9pHAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T08:05:21.908791Z"},"content_sha256":"04e99c757048fce6bd029615433a1857af7f469e9b4800744d57a52ef9bc9649","schema_version":"1.0","event_id":"sha256:04e99c757048fce6bd029615433a1857af7f469e9b4800744d57a52ef9bc9649"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY/bundle.json","state_url":"https://pith.science/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-28T08:05:21Z","links":{"resolver":"https://pith.science/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY","bundle":"https://pith.science/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY/bundle.json","state":"https://pith.science/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z2PIALJXKCI6UZVDDYVDWKCUUY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:Z2PIALJXKCI6UZVDDYVDWKCUUY","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":"0f98330fbc80e400d9ceae5ff6806ed7c0926b6aafa29cff5cec6b5fd7cef7a9","cross_cats_sorted":["cs.SY","math.OC"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-04T08:26:14Z","title_canon_sha256":"b07957ac130b41fde7fd20f317d6988179cc27c3c42d61fbd43d3bc5fab46b2d"},"schema_version":"1.0","source":{"id":"2403.01830","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.01830","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"arxiv_version","alias_value":"2403.01830v1","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.01830","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"pith_short_12","alias_value":"Z2PIALJXKCI6","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"pith_short_16","alias_value":"Z2PIALJXKCI6UZVD","created_at":"2026-07-05T07:51:52Z"},{"alias_kind":"pith_short_8","alias_value":"Z2PIALJX","created_at":"2026-07-05T07:51:52Z"}],"graph_snapshots":[{"event_id":"sha256:04e99c757048fce6bd029615433a1857af7f469e9b4800744d57a52ef9bc9649","target":"graph","created_at":"2026-07-05T07:51:52Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2403.01830/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Nonlinear model predictive control (NMPC) is a popular strategy for solving motion planning problems, including obstacle avoidance constraints, in autonomous driving applications. Non-smooth obstacle shapes, such as rectangles, introduce additional local minima in the underlying optimization problem. Smooth over-approximations, e.g., ellipsoidal shapes, limit the performance due to their conservativeness. We propose to vary the smoothness and the related over-approximation by a homotopy. Instead of varying the smoothness in consecutive sequential quadratic programming iterations, we use formul","authors_text":"Katrin Baumg\\\"artner, Moritz Diehl, Rien Quirynen, Rudolf Reiter","cross_cats":["cs.SY","math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-04T08:26:14Z","title":"Progressive Smoothing for Motion Planning in Real-Time NMPC"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.01830","kind":"arxiv","version":1},"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":"sha256:5a931b0fa7aa6bdaf7f64ed19c3de617cd0d73144e0aaf69dd7138677d8da08b","target":"record","created_at":"2026-07-05T07:51:52Z","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":"0f98330fbc80e400d9ceae5ff6806ed7c0926b6aafa29cff5cec6b5fd7cef7a9","cross_cats_sorted":["cs.SY","math.OC"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-04T08:26:14Z","title_canon_sha256":"b07957ac130b41fde7fd20f317d6988179cc27c3c42d61fbd43d3bc5fab46b2d"},"schema_version":"1.0","source":{"id":"2403.01830","kind":"arxiv","version":1}},"canonical_sha256":"ce9e802d375091ea66a31e2a3b2854a61382e482152f9a1702f8b2f155cad0a7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ce9e802d375091ea66a31e2a3b2854a61382e482152f9a1702f8b2f155cad0a7","first_computed_at":"2026-07-05T07:51:52.541541Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:51:52.541541Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qJZJ5RxvRRn+cm3u7/IUPx7o+CxBpTxcXASgrZx6T5f7e2R4xHlCLrB/9vlyjSdDz58SlSmNajyCwImJ2L0CDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:51:52.541972Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.01830","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a931b0fa7aa6bdaf7f64ed19c3de617cd0d73144e0aaf69dd7138677d8da08b","sha256:04e99c757048fce6bd029615433a1857af7f469e9b4800744d57a52ef9bc9649"],"state_sha256":"a65799952bff9a2e7e030b7e2c88c44a2f80583a33429d38da41c3709da4797c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mNupR2XL8kFJCYQQCs0Y8LEV17Khbty4czuNvzM0JyjvbWdCYjY0VSgibltSYaxL9jK3GksmDUU9MqF8/pOADw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T08:05:21.911418Z","bundle_sha256":"639cf8a927df0a67c1c0cccdaa91e2aa39effc0e82a13f371f77f7b76a218402"}}