{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QBHBW6OUMEH6AJTVCKLX2DJEFY","short_pith_number":"pith:QBHBW6OU","schema_version":"1.0","canonical_sha256":"804e1b79d4610fe0267512977d0d242e3209bfe27bc9c6ec8ec697a37e68499c","source":{"kind":"arxiv","id":"2309.11655","version":1},"attestation_state":"computed","paper":{"title":"Achieving Autonomous Cloth Manipulation with Optimal Control via Differentiable Physics-Aware Regularization and Safety Constraints","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Fei Liu, Michael Yip, Xiao Liang, Yutong Zhang","submitted_at":"2023-09-20T21:41:01Z","abstract_excerpt":"Cloth manipulation is a category of deformable object manipulation of great interest to the robotics community, from applications of automated laundry-folding and home organizing and cleaning to textiles and flexible manufacturing. Despite the desire for automated cloth manipulation, the thin-shell dynamics and under-actuation nature of cloth present significant challenges for robots to effectively interact with them. Many recent works omit explicit modeling in favor of learning-based methods that may yield control policies directly. However, these methods require large training sets that must"},"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":"2309.11655","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-09-20T21:41:01Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"e05c90a8183edc686d83a792ecb4cf2859a2b2a6509def82653069d043d36888","abstract_canon_sha256":"7c5bef82ca454c48cb4dbf63cab67970804fef42114715e5619b2639b4886102"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:52:52.686712Z","signature_b64":"e9uvKAWJC4Mr9ZtHAcFbgU3Xh4ci50TBCTF+S0zV3oK62rvwajBBi0SrKbCZxWV/0gjrUdvMnJQQvMtgZQojAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"804e1b79d4610fe0267512977d0d242e3209bfe27bc9c6ec8ec697a37e68499c","last_reissued_at":"2026-07-05T06:52:52.686232Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:52:52.686232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Achieving Autonomous Cloth Manipulation with Optimal Control via Differentiable Physics-Aware Regularization and Safety Constraints","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Fei Liu, Michael Yip, Xiao Liang, Yutong Zhang","submitted_at":"2023-09-20T21:41:01Z","abstract_excerpt":"Cloth manipulation is a category of deformable object manipulation of great interest to the robotics community, from applications of automated laundry-folding and home organizing and cleaning to textiles and flexible manufacturing. Despite the desire for automated cloth manipulation, the thin-shell dynamics and under-actuation nature of cloth present significant challenges for robots to effectively interact with them. Many recent works omit explicit modeling in favor of learning-based methods that may yield control policies directly. However, these methods require large training sets that must"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.11655","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/2309.11655/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2309.11655","created_at":"2026-07-05T06:52:52.686287+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.11655v1","created_at":"2026-07-05T06:52:52.686287+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.11655","created_at":"2026-07-05T06:52:52.686287+00:00"},{"alias_kind":"pith_short_12","alias_value":"QBHBW6OUMEH6","created_at":"2026-07-05T06:52:52.686287+00:00"},{"alias_kind":"pith_short_16","alias_value":"QBHBW6OUMEH6AJTV","created_at":"2026-07-05T06:52:52.686287+00:00"},{"alias_kind":"pith_short_8","alias_value":"QBHBW6OU","created_at":"2026-07-05T06:52:52.686287+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2603.14634","citing_title":"Physically Accurate Rigid-Body Dynamics in Particle-Based Simulation","ref_index":9,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY","json":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY.json","graph_json":"https://pith.science/api/pith-number/QBHBW6OUMEH6AJTVCKLX2DJEFY/graph.json","events_json":"https://pith.science/api/pith-number/QBHBW6OUMEH6AJTVCKLX2DJEFY/events.json","paper":"https://pith.science/paper/QBHBW6OU"},"agent_actions":{"view_html":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY","download_json":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY.json","view_paper":"https://pith.science/paper/QBHBW6OU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.11655&json=true","fetch_graph":"https://pith.science/api/pith-number/QBHBW6OUMEH6AJTVCKLX2DJEFY/graph.json","fetch_events":"https://pith.science/api/pith-number/QBHBW6OUMEH6AJTVCKLX2DJEFY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY/action/storage_attestation","attest_author":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY/action/author_attestation","sign_citation":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY/action/citation_signature","submit_replication":"https://pith.science/pith/QBHBW6OUMEH6AJTVCKLX2DJEFY/action/replication_record"}},"created_at":"2026-07-05T06:52:52.686287+00:00","updated_at":"2026-07-05T06:52:52.686287+00:00"}