{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:GC3U2LV6FFPGDBMO3SQUH7K3EM","short_pith_number":"pith:GC3U2LV6","canonical_record":{"source":{"id":"1901.03557","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-01-11T11:25:52Z","cross_cats_sorted":[],"title_canon_sha256":"7ec9ce8f7ca7b69a7e6b493203e6a57289e4492c0ad90d0b1e0f2eadf6546929","abstract_canon_sha256":"e1a523da125919f55295964352d28883fcc77726a70e8aa898880269c48769d3"},"schema_version":"1.0"},"canonical_sha256":"30b74d2ebe295e61858edca143fd5b233d2acf3fa2d80561f72c084d8f1586f6","source":{"kind":"arxiv","id":"1901.03557","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.03557","created_at":"2026-05-17T23:56:30Z"},{"alias_kind":"arxiv_version","alias_value":"1901.03557v1","created_at":"2026-05-17T23:56:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.03557","created_at":"2026-05-17T23:56:30Z"},{"alias_kind":"pith_short_12","alias_value":"GC3U2LV6FFPG","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"GC3U2LV6FFPGDBMO","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"GC3U2LV6","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:GC3U2LV6FFPGDBMO3SQUH7K3EM","target":"record","payload":{"canonical_record":{"source":{"id":"1901.03557","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-01-11T11:25:52Z","cross_cats_sorted":[],"title_canon_sha256":"7ec9ce8f7ca7b69a7e6b493203e6a57289e4492c0ad90d0b1e0f2eadf6546929","abstract_canon_sha256":"e1a523da125919f55295964352d28883fcc77726a70e8aa898880269c48769d3"},"schema_version":"1.0"},"canonical_sha256":"30b74d2ebe295e61858edca143fd5b233d2acf3fa2d80561f72c084d8f1586f6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:30.915350Z","signature_b64":"ARE1Ngd5jteq/EQmGzmmx1MlQZkFS10UjV+SAgmFeqhArpOPhu8Y40YPRYvGJSkkmJtyUqyZ0IkzwR0oIeSlBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30b74d2ebe295e61858edca143fd5b233d2acf3fa2d80561f72c084d8f1586f6","last_reissued_at":"2026-05-17T23:56:30.914819Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:30.914819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.03557","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":"2026-05-17T23:56:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gDu1ZiHRG0m5nB9brA39JkS6DI6th6tuk/Q67Tt79T58tDcEzvaxvNcDYstPjQSgloqioD1edxiH3Fj/Py7rCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:35:51.562199Z"},"content_sha256":"da905665b156e126840efab3630bb3c02a379c065e75dfe871dd748527e2c33d","schema_version":"1.0","event_id":"sha256:da905665b156e126840efab3630bb3c02a379c065e75dfe871dd748527e2c33d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:GC3U2LV6FFPGDBMO3SQUH7K3EM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Manipulation States and Actions for Efficient Non-prehensile Rearrangement Planning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Danica Kragic, Isac Arnekvist, Johannes Stork, Joshua A. Haustein, Kaiyu Hang","submitted_at":"2019-01-11T11:25:52Z","abstract_excerpt":"This paper addresses non-prehensile rearrangement planning problems where a robot is tasked to rearrange objects among obstacles on a planar surface. We present an efficient planning algorithm that is designed to impose few assumptions on the robot's non-prehensile manipulation abilities and is simple to adapt to different robot embodiments. For this, we combine sampling-based motion planning with reinforcement learning and generative modeling. Our algorithm explores the composite configuration space of objects and robot as a search over robot actions, forward simulated in a physics model. Thi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.03557","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":"2026-05-17T23:56:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lCqTbVcIiiP5h7V7+ufSggzWUwIArBHsIYdOe/uyB+fhUhTKBUSm3wnfSKC10g4sypeWVwzywHzNip11fuz/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:35:51.562594Z"},"content_sha256":"d2923b46ceef40e42fe527f4e998456d37f0d738f9ed0568f04c83f30ccda492","schema_version":"1.0","event_id":"sha256:d2923b46ceef40e42fe527f4e998456d37f0d738f9ed0568f04c83f30ccda492"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM/bundle.json","state_url":"https://pith.science/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM/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":"2026-05-30T13:35:51Z","links":{"resolver":"https://pith.science/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM","bundle":"https://pith.science/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM/bundle.json","state":"https://pith.science/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GC3U2LV6FFPGDBMO3SQUH7K3EM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:GC3U2LV6FFPGDBMO3SQUH7K3EM","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":"e1a523da125919f55295964352d28883fcc77726a70e8aa898880269c48769d3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-01-11T11:25:52Z","title_canon_sha256":"7ec9ce8f7ca7b69a7e6b493203e6a57289e4492c0ad90d0b1e0f2eadf6546929"},"schema_version":"1.0","source":{"id":"1901.03557","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.03557","created_at":"2026-05-17T23:56:30Z"},{"alias_kind":"arxiv_version","alias_value":"1901.03557v1","created_at":"2026-05-17T23:56:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.03557","created_at":"2026-05-17T23:56:30Z"},{"alias_kind":"pith_short_12","alias_value":"GC3U2LV6FFPG","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"GC3U2LV6FFPGDBMO","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"GC3U2LV6","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:d2923b46ceef40e42fe527f4e998456d37f0d738f9ed0568f04c83f30ccda492","target":"graph","created_at":"2026-05-17T23:56:30Z","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 addresses non-prehensile rearrangement planning problems where a robot is tasked to rearrange objects among obstacles on a planar surface. We present an efficient planning algorithm that is designed to impose few assumptions on the robot's non-prehensile manipulation abilities and is simple to adapt to different robot embodiments. For this, we combine sampling-based motion planning with reinforcement learning and generative modeling. Our algorithm explores the composite configuration space of objects and robot as a search over robot actions, forward simulated in a physics model. Thi","authors_text":"Danica Kragic, Isac Arnekvist, Johannes Stork, Joshua A. Haustein, Kaiyu Hang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-01-11T11:25:52Z","title":"Learning Manipulation States and Actions for Efficient Non-prehensile Rearrangement Planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.03557","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:da905665b156e126840efab3630bb3c02a379c065e75dfe871dd748527e2c33d","target":"record","created_at":"2026-05-17T23:56:30Z","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":"e1a523da125919f55295964352d28883fcc77726a70e8aa898880269c48769d3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-01-11T11:25:52Z","title_canon_sha256":"7ec9ce8f7ca7b69a7e6b493203e6a57289e4492c0ad90d0b1e0f2eadf6546929"},"schema_version":"1.0","source":{"id":"1901.03557","kind":"arxiv","version":1}},"canonical_sha256":"30b74d2ebe295e61858edca143fd5b233d2acf3fa2d80561f72c084d8f1586f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30b74d2ebe295e61858edca143fd5b233d2acf3fa2d80561f72c084d8f1586f6","first_computed_at":"2026-05-17T23:56:30.914819Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:30.914819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ARE1Ngd5jteq/EQmGzmmx1MlQZkFS10UjV+SAgmFeqhArpOPhu8Y40YPRYvGJSkkmJtyUqyZ0IkzwR0oIeSlBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:30.915350Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.03557","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:da905665b156e126840efab3630bb3c02a379c065e75dfe871dd748527e2c33d","sha256:d2923b46ceef40e42fe527f4e998456d37f0d738f9ed0568f04c83f30ccda492"],"state_sha256":"339cf867df96c48f21f633930e69ebdec110a87b443b52c9de2fe558162a502e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1MwsktPKQFdDoxcdr0g3pDWeWTsw6sW9yT3BEwZuj7pnPXpLDtOgqUQsraXqcZbZJ2dDZ1ECs7V0ZC6xmmM8DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T13:35:51.564713Z","bundle_sha256":"a77a0ef1ca4124d9b05f337c2af8d123137be49f74bf5dd0e1bc55be458791e2"}}