{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:XDNQKS2OS5UFLI57MT7A7NQVEA","short_pith_number":"pith:XDNQKS2O","canonical_record":{"source":{"id":"1902.09157","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-02-25T09:20:20Z","cross_cats_sorted":[],"title_canon_sha256":"08450ad0c613efc2605ff84e5b972c52b25904df5d6dcea62abc1a63fdda4b43","abstract_canon_sha256":"88ae47bf5621c003d58345430360447611b93229ef51673f25fbb140f6ee2132"},"schema_version":"1.0"},"canonical_sha256":"b8db054b4e976855a3bf64fe0fb615201536cff7ee7dd00f53b4bb568b2ad6d6","source":{"kind":"arxiv","id":"1902.09157","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.09157","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"arxiv_version","alias_value":"1902.09157v1","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.09157","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"pith_short_12","alias_value":"XDNQKS2OS5UF","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"XDNQKS2OS5UFLI57","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"XDNQKS2O","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:XDNQKS2OS5UFLI57MT7A7NQVEA","target":"record","payload":{"canonical_record":{"source":{"id":"1902.09157","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-02-25T09:20:20Z","cross_cats_sorted":[],"title_canon_sha256":"08450ad0c613efc2605ff84e5b972c52b25904df5d6dcea62abc1a63fdda4b43","abstract_canon_sha256":"88ae47bf5621c003d58345430360447611b93229ef51673f25fbb140f6ee2132"},"schema_version":"1.0"},"canonical_sha256":"b8db054b4e976855a3bf64fe0fb615201536cff7ee7dd00f53b4bb568b2ad6d6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:46.492925Z","signature_b64":"unsTU2BXEjpSAulJwx6AeiGLjgIAeSeFKA7aLu9gFzryD9ojcFqsQSl8biheyAqeUR9t5z6u63zSHm1tjEbYDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8db054b4e976855a3bf64fe0fb615201536cff7ee7dd00f53b4bb568b2ad6d6","last_reissued_at":"2026-05-17T23:52:46.492391Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:46.492391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.09157","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":"2026-05-17T23:52:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GrwlLJH3wfT05SkLbZ/YLQSTxFgZ7ZQ0RQtrPgA4YFahChX+dOZtY6ztqsfl+10EXldtFEPOKD3AJZmgrs+MDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T10:32:09.807801Z"},"content_sha256":"b2590bbcb10d63592a9731844d5453d2eb1752ca0346d46dcf861698de7541b4","schema_version":"1.0","event_id":"sha256:b2590bbcb10d63592a9731844d5453d2eb1752ca0346d46dcf861698de7541b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:XDNQKS2OS5UFLI57MT7A7NQVEA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Joshua C. Triyonoputro, Kensuke Harada, Weiwei Wan","submitted_at":"2019-02-25T09:20:20Z","abstract_excerpt":"This paper uses robots to assemble pegs into holes on surfaces with different colors and textures. It especially targets at the problem of peg-in-hole assembly with initial position uncertainty. Two in-hand cameras and a force-torque sensor are used to account for the position uncertainty. A program sequence comprising learning-based visual servoing, spiral search, and impedance control is implemented to perform the peg-in-hole task with feedback from the above sensors. Contributions are mainly made in the learning-based visual servoing of the sequence, where a deep neural network is trained w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.09157","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":""},"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":"2026-05-17T23:52:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vFXGSW7BRNYXbj2LAgh4h9FJoDEXNLzvS2U3wPGX0FS9dvL9Q861MqHzfz38xvDm9JVtQkUWGwuZcxZoUuveCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T10:32:09.808487Z"},"content_sha256":"c9d9b906dafff0dd9e86793eb5f9dadfba5ccabceac396c9efc2367a5628df34","schema_version":"1.0","event_id":"sha256:c9d9b906dafff0dd9e86793eb5f9dadfba5ccabceac396c9efc2367a5628df34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XDNQKS2OS5UFLI57MT7A7NQVEA/bundle.json","state_url":"https://pith.science/pith/XDNQKS2OS5UFLI57MT7A7NQVEA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XDNQKS2OS5UFLI57MT7A7NQVEA/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":"2026-05-22T10:32:09Z","links":{"resolver":"https://pith.science/pith/XDNQKS2OS5UFLI57MT7A7NQVEA","bundle":"https://pith.science/pith/XDNQKS2OS5UFLI57MT7A7NQVEA/bundle.json","state":"https://pith.science/pith/XDNQKS2OS5UFLI57MT7A7NQVEA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XDNQKS2OS5UFLI57MT7A7NQVEA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:XDNQKS2OS5UFLI57MT7A7NQVEA","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":"88ae47bf5621c003d58345430360447611b93229ef51673f25fbb140f6ee2132","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-02-25T09:20:20Z","title_canon_sha256":"08450ad0c613efc2605ff84e5b972c52b25904df5d6dcea62abc1a63fdda4b43"},"schema_version":"1.0","source":{"id":"1902.09157","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.09157","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"arxiv_version","alias_value":"1902.09157v1","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.09157","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"pith_short_12","alias_value":"XDNQKS2OS5UF","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"XDNQKS2OS5UFLI57","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"XDNQKS2O","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:c9d9b906dafff0dd9e86793eb5f9dadfba5ccabceac396c9efc2367a5628df34","target":"graph","created_at":"2026-05-17T23:52:46Z","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"},"paper":{"abstract_excerpt":"This paper uses robots to assemble pegs into holes on surfaces with different colors and textures. It especially targets at the problem of peg-in-hole assembly with initial position uncertainty. Two in-hand cameras and a force-torque sensor are used to account for the position uncertainty. A program sequence comprising learning-based visual servoing, spiral search, and impedance control is implemented to perform the peg-in-hole task with feedback from the above sensors. Contributions are mainly made in the learning-based visual servoing of the sequence, where a deep neural network is trained w","authors_text":"Joshua C. Triyonoputro, Kensuke Harada, Weiwei Wan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-02-25T09:20:20Z","title":"Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.09157","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:b2590bbcb10d63592a9731844d5453d2eb1752ca0346d46dcf861698de7541b4","target":"record","created_at":"2026-05-17T23:52:46Z","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":"88ae47bf5621c003d58345430360447611b93229ef51673f25fbb140f6ee2132","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-02-25T09:20:20Z","title_canon_sha256":"08450ad0c613efc2605ff84e5b972c52b25904df5d6dcea62abc1a63fdda4b43"},"schema_version":"1.0","source":{"id":"1902.09157","kind":"arxiv","version":1}},"canonical_sha256":"b8db054b4e976855a3bf64fe0fb615201536cff7ee7dd00f53b4bb568b2ad6d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b8db054b4e976855a3bf64fe0fb615201536cff7ee7dd00f53b4bb568b2ad6d6","first_computed_at":"2026-05-17T23:52:46.492391Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:46.492391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"unsTU2BXEjpSAulJwx6AeiGLjgIAeSeFKA7aLu9gFzryD9ojcFqsQSl8biheyAqeUR9t5z6u63zSHm1tjEbYDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:46.492925Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.09157","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b2590bbcb10d63592a9731844d5453d2eb1752ca0346d46dcf861698de7541b4","sha256:c9d9b906dafff0dd9e86793eb5f9dadfba5ccabceac396c9efc2367a5628df34"],"state_sha256":"a7fc0b10a97b2f3e978bcaa677293cbd34b9bd9d0baf98600c2b6df300277ac7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mIFs+SZuysCAlhoeV0a2YC/+O1ydXqXEdtRhdlIlao5H6KL05zZgC5eEbf6rVE9qQRvU0SUX5OOdAPSR4ouMAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T10:32:09.811534Z","bundle_sha256":"b8da919634312f3ceebf81cad757c61d686a3b579d1fad96eb6514fb38f70ff4"}}