{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:RGBJYUIBBSXZNU3KBOOHXZFWEQ","short_pith_number":"pith:RGBJYUIB","schema_version":"1.0","canonical_sha256":"89829c51010caf96d36a0b9c7be4b6242bb9caea2afc1c794ea41a922c34de58","source":{"kind":"arxiv","id":"2112.05941","version":4},"attestation_state":"computed","paper":{"title":"Learning Efficient Policies for Picking Entangled Wire Harnesses: An Approach to Industrial Bin Picking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Kensuke Harada, Weiwei Wan, Xinyi Zhang, Yukiyasu Domae","submitted_at":"2021-12-11T10:01:39Z","abstract_excerpt":"Wire harnesses are essential connecting components in manufacturing industry but are challenging to be automated in industrial tasks such as bin picking. They are long, flexible and tend to get entangled when randomly placed in a bin. This makes it difficult for the robot to grasp a single one in dense clutter. Besides, training or collecting data in simulation is challenging due to the difficulties in modeling the combination of deformable and rigid components for wire harnesses. In this work, instead of directly lifting wire harnesses, we propose to grasp and extract the target following a c"},"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":"2112.05941","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-12-11T10:01:39Z","cross_cats_sorted":[],"title_canon_sha256":"0126b4e901b4cc1244ecacb95e2384842ef7b571d738df29495bbe0b83172f25","abstract_canon_sha256":"5387e83bc5ddf99b49a8be1c221b54fc11e85a665ae3fd2ea61d32f90f974508"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:31:12.009304Z","signature_b64":"EHd031IpGsUlP3g9yA4X717LmjRQ5hrNmVqAtSyWkYD1/S0DxYBNtfrM7Ma/owSD1HKaHLibM4516IQy4NXJAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"89829c51010caf96d36a0b9c7be4b6242bb9caea2afc1c794ea41a922c34de58","last_reissued_at":"2026-07-05T05:31:12.008868Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:31:12.008868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Efficient Policies for Picking Entangled Wire Harnesses: An Approach to Industrial Bin Picking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Kensuke Harada, Weiwei Wan, Xinyi Zhang, Yukiyasu Domae","submitted_at":"2021-12-11T10:01:39Z","abstract_excerpt":"Wire harnesses are essential connecting components in manufacturing industry but are challenging to be automated in industrial tasks such as bin picking. They are long, flexible and tend to get entangled when randomly placed in a bin. This makes it difficult for the robot to grasp a single one in dense clutter. Besides, training or collecting data in simulation is challenging due to the difficulties in modeling the combination of deformable and rigid components for wire harnesses. In this work, instead of directly lifting wire harnesses, we propose to grasp and extract the target following a c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.05941","kind":"arxiv","version":4},"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/2112.05941/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":"2112.05941","created_at":"2026-07-05T05:31:12.008924+00:00"},{"alias_kind":"arxiv_version","alias_value":"2112.05941v4","created_at":"2026-07-05T05:31:12.008924+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.05941","created_at":"2026-07-05T05:31:12.008924+00:00"},{"alias_kind":"pith_short_12","alias_value":"RGBJYUIBBSXZ","created_at":"2026-07-05T05:31:12.008924+00:00"},{"alias_kind":"pith_short_16","alias_value":"RGBJYUIBBSXZNU3K","created_at":"2026-07-05T05:31:12.008924+00:00"},{"alias_kind":"pith_short_8","alias_value":"RGBJYUIB","created_at":"2026-07-05T05:31:12.008924+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/RGBJYUIBBSXZNU3KBOOHXZFWEQ","json":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ.json","graph_json":"https://pith.science/api/pith-number/RGBJYUIBBSXZNU3KBOOHXZFWEQ/graph.json","events_json":"https://pith.science/api/pith-number/RGBJYUIBBSXZNU3KBOOHXZFWEQ/events.json","paper":"https://pith.science/paper/RGBJYUIB"},"agent_actions":{"view_html":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ","download_json":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ.json","view_paper":"https://pith.science/paper/RGBJYUIB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2112.05941&json=true","fetch_graph":"https://pith.science/api/pith-number/RGBJYUIBBSXZNU3KBOOHXZFWEQ/graph.json","fetch_events":"https://pith.science/api/pith-number/RGBJYUIBBSXZNU3KBOOHXZFWEQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ/action/storage_attestation","attest_author":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ/action/author_attestation","sign_citation":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ/action/citation_signature","submit_replication":"https://pith.science/pith/RGBJYUIBBSXZNU3KBOOHXZFWEQ/action/replication_record"}},"created_at":"2026-07-05T05:31:12.008924+00:00","updated_at":"2026-07-05T05:31:12.008924+00:00"}