{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:I66AVNLEBOEVW42W3FGS7YPTPH","short_pith_number":"pith:I66AVNLE","schema_version":"1.0","canonical_sha256":"47bc0ab5640b895b7356d94d2fe1f379fdec477735d087367c6a640130056387","source":{"kind":"arxiv","id":"2303.04705","version":1},"attestation_state":"computed","paper":{"title":"Dextrous Tactile In-Hand Manipulation Using a Modular Reinforcement Learning Architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Berthold B\\\"auml, Johannes Pitz, Lennart R\\\"ostel, Leon Sievers","submitted_at":"2023-03-08T16:45:18Z","abstract_excerpt":"Dextrous in-hand manipulation with a multi-fingered robotic hand is a challenging task, esp. when performed with the hand oriented upside down, demanding permanent force-closure, and when no external sensors are used. For the task of reorienting an object to a given goal orientation (vs. infinitely spinning it around an axis), the lack of external sensors is an additional fundamental challenge as the state of the object has to be estimated all the time, e.g., to detect when the goal is reached. In this paper, we show that the task of reorienting a cube to any of the 24 possible goal orientatio"},"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":"2303.04705","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-03-08T16:45:18Z","cross_cats_sorted":[],"title_canon_sha256":"5a79199744bc20c2dd2f7ad502afd952ee5790e25837d8644de3a510a90da29c","abstract_canon_sha256":"e133d88ae0964af63c2156da028ae096c3de8e867d71dff57e4b5df5dcc5541f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:09:46.477116Z","signature_b64":"POqsFEPCBzpfvj1WGKqy74mh36V7OUlL5eiB0aIYvXc8FZ/vE5uBhYpnLTZoUf8nDzBthRhgZ5nh0GZhARdkBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47bc0ab5640b895b7356d94d2fe1f379fdec477735d087367c6a640130056387","last_reissued_at":"2026-07-05T07:09:46.476640Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:09:46.476640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dextrous Tactile In-Hand Manipulation Using a Modular Reinforcement Learning Architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Berthold B\\\"auml, Johannes Pitz, Lennart R\\\"ostel, Leon Sievers","submitted_at":"2023-03-08T16:45:18Z","abstract_excerpt":"Dextrous in-hand manipulation with a multi-fingered robotic hand is a challenging task, esp. when performed with the hand oriented upside down, demanding permanent force-closure, and when no external sensors are used. For the task of reorienting an object to a given goal orientation (vs. infinitely spinning it around an axis), the lack of external sensors is an additional fundamental challenge as the state of the object has to be estimated all the time, e.g., to detect when the goal is reached. In this paper, we show that the task of reorienting a cube to any of the 24 possible goal orientatio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.04705","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/2303.04705/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":"2303.04705","created_at":"2026-07-05T07:09:46.476695+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.04705v1","created_at":"2026-07-05T07:09:46.476695+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.04705","created_at":"2026-07-05T07:09:46.476695+00:00"},{"alias_kind":"pith_short_12","alias_value":"I66AVNLEBOEV","created_at":"2026-07-05T07:09:46.476695+00:00"},{"alias_kind":"pith_short_16","alias_value":"I66AVNLEBOEVW42W","created_at":"2026-07-05T07:09:46.476695+00:00"},{"alias_kind":"pith_short_8","alias_value":"I66AVNLE","created_at":"2026-07-05T07:09:46.476695+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2603.04531","citing_title":"PTLD: Sim-to-real Privileged Tactile Latent Distillation for Dexterous Manipulation","ref_index":13,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH","json":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH.json","graph_json":"https://pith.science/api/pith-number/I66AVNLEBOEVW42W3FGS7YPTPH/graph.json","events_json":"https://pith.science/api/pith-number/I66AVNLEBOEVW42W3FGS7YPTPH/events.json","paper":"https://pith.science/paper/I66AVNLE"},"agent_actions":{"view_html":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH","download_json":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH.json","view_paper":"https://pith.science/paper/I66AVNLE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.04705&json=true","fetch_graph":"https://pith.science/api/pith-number/I66AVNLEBOEVW42W3FGS7YPTPH/graph.json","fetch_events":"https://pith.science/api/pith-number/I66AVNLEBOEVW42W3FGS7YPTPH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH/action/storage_attestation","attest_author":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH/action/author_attestation","sign_citation":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH/action/citation_signature","submit_replication":"https://pith.science/pith/I66AVNLEBOEVW42W3FGS7YPTPH/action/replication_record"}},"created_at":"2026-07-05T07:09:46.476695+00:00","updated_at":"2026-07-05T07:09:46.476695+00:00"}