{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:P3M5BKEPWT7BDIXDXRRHKZ7ODZ","short_pith_number":"pith:P3M5BKEP","canonical_record":{"source":{"id":"2409.19920","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-30T03:49:05Z","cross_cats_sorted":[],"title_canon_sha256":"80a7c3506a2046419f705015e05861b6a3444dbf90d4233e3b241a000abe0e15","abstract_canon_sha256":"38f6cc034963438751cdc853b044f129952ca1d3f219f969b35ecaf79490957e"},"schema_version":"1.0"},"canonical_sha256":"7ed9d0a88fb4fe11a2e3bc627567ee1e648afe4e75c38815aac93c90e5bb304b","source":{"kind":"arxiv","id":"2409.19920","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.19920","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"arxiv_version","alias_value":"2409.19920v3","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.19920","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"pith_short_12","alias_value":"P3M5BKEPWT7B","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"pith_short_16","alias_value":"P3M5BKEPWT7BDIXD","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"pith_short_8","alias_value":"P3M5BKEP","created_at":"2026-07-05T10:33:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:P3M5BKEPWT7BDIXDXRRHKZ7ODZ","target":"record","payload":{"canonical_record":{"source":{"id":"2409.19920","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-30T03:49:05Z","cross_cats_sorted":[],"title_canon_sha256":"80a7c3506a2046419f705015e05861b6a3444dbf90d4233e3b241a000abe0e15","abstract_canon_sha256":"38f6cc034963438751cdc853b044f129952ca1d3f219f969b35ecaf79490957e"},"schema_version":"1.0"},"canonical_sha256":"7ed9d0a88fb4fe11a2e3bc627567ee1e648afe4e75c38815aac93c90e5bb304b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:33:05.605974Z","signature_b64":"CTi6uLoZjETVu7H3NfbxRU56TeszNMwgAzZdZQtW59HVULWaasRV2DlJobzMelHR+V+9q2WZkevIZGdgzrrvDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ed9d0a88fb4fe11a2e3bc627567ee1e648afe4e75c38815aac93c90e5bb304b","last_reissued_at":"2026-07-05T10:33:05.605481Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:33:05.605481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.19920","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:33:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OrYQWEcmMxVy/H5Z5QTPcSHIC/h7kpSmnUTH6y1OEhwmdjUqdqKrX49VHxjhxHsLJTY899+XCmFiTiUVxTTODg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T03:46:13.253289Z"},"content_sha256":"a89ca8dfb97a54bdab393696533b63228673bce034147fe35f973672b952212b","schema_version":"1.0","event_id":"sha256:a89ca8dfb97a54bdab393696533b63228673bce034147fe35f973672b952212b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:P3M5BKEPWT7BDIXDXRRHKZ7ODZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Playful DoggyBot: Learning Agile and Precise Quadrupedal Locomotion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Hang Zhao, Soeren Schwertfeger, Xin Duan, Ziwen Zhuang","submitted_at":"2024-09-30T03:49:05Z","abstract_excerpt":"Quadrupedal animals can perform agile and playful tasks while interacting with real-world objects. For instance, a trained dog can track and catch a flying frisbee before it touches the ground, while a cat left alone at home may leap to grasp the door handle. Successfully grasping an object during high-dynamic locomotion requires highly precise perception and control. However, due to hardware limitations, agility and precision are usually a trade-off in robotics problems. In this work, we employ a perception-control decoupled system based on Reinforcement Learning (RL), aiming to explore the l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.19920","kind":"arxiv","version":3},"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/2409.19920/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:33:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZLNzPzB0tnncdD47mprhcu5mq23BCa0VlWXaCCjlOS84KQgKbSNELWBFSJEo9Y35ahgjez5bef2FVJfYF5SjCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T03:46:13.253681Z"},"content_sha256":"eb99f6c2162d7aae91b1a43e07dfe5dddf73713d98eb7f3bb2a11229411c450f","schema_version":"1.0","event_id":"sha256:eb99f6c2162d7aae91b1a43e07dfe5dddf73713d98eb7f3bb2a11229411c450f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ/bundle.json","state_url":"https://pith.science/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ/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":"2026-07-24T03:46:13Z","links":{"resolver":"https://pith.science/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ","bundle":"https://pith.science/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ/bundle.json","state":"https://pith.science/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P3M5BKEPWT7BDIXDXRRHKZ7ODZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:P3M5BKEPWT7BDIXDXRRHKZ7ODZ","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":"38f6cc034963438751cdc853b044f129952ca1d3f219f969b35ecaf79490957e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-30T03:49:05Z","title_canon_sha256":"80a7c3506a2046419f705015e05861b6a3444dbf90d4233e3b241a000abe0e15"},"schema_version":"1.0","source":{"id":"2409.19920","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.19920","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"arxiv_version","alias_value":"2409.19920v3","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.19920","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"pith_short_12","alias_value":"P3M5BKEPWT7B","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"pith_short_16","alias_value":"P3M5BKEPWT7BDIXD","created_at":"2026-07-05T10:33:05Z"},{"alias_kind":"pith_short_8","alias_value":"P3M5BKEP","created_at":"2026-07-05T10:33:05Z"}],"graph_snapshots":[{"event_id":"sha256:eb99f6c2162d7aae91b1a43e07dfe5dddf73713d98eb7f3bb2a11229411c450f","target":"graph","created_at":"2026-07-05T10:33:05Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2409.19920/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quadrupedal animals can perform agile and playful tasks while interacting with real-world objects. For instance, a trained dog can track and catch a flying frisbee before it touches the ground, while a cat left alone at home may leap to grasp the door handle. Successfully grasping an object during high-dynamic locomotion requires highly precise perception and control. However, due to hardware limitations, agility and precision are usually a trade-off in robotics problems. In this work, we employ a perception-control decoupled system based on Reinforcement Learning (RL), aiming to explore the l","authors_text":"Hang Zhao, Soeren Schwertfeger, Xin Duan, Ziwen Zhuang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-30T03:49:05Z","title":"Playful DoggyBot: Learning Agile and Precise Quadrupedal Locomotion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.19920","kind":"arxiv","version":3},"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:a89ca8dfb97a54bdab393696533b63228673bce034147fe35f973672b952212b","target":"record","created_at":"2026-07-05T10:33:05Z","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":"38f6cc034963438751cdc853b044f129952ca1d3f219f969b35ecaf79490957e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-30T03:49:05Z","title_canon_sha256":"80a7c3506a2046419f705015e05861b6a3444dbf90d4233e3b241a000abe0e15"},"schema_version":"1.0","source":{"id":"2409.19920","kind":"arxiv","version":3}},"canonical_sha256":"7ed9d0a88fb4fe11a2e3bc627567ee1e648afe4e75c38815aac93c90e5bb304b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ed9d0a88fb4fe11a2e3bc627567ee1e648afe4e75c38815aac93c90e5bb304b","first_computed_at":"2026-07-05T10:33:05.605481Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:33:05.605481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CTi6uLoZjETVu7H3NfbxRU56TeszNMwgAzZdZQtW59HVULWaasRV2DlJobzMelHR+V+9q2WZkevIZGdgzrrvDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:33:05.605974Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.19920","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a89ca8dfb97a54bdab393696533b63228673bce034147fe35f973672b952212b","sha256:eb99f6c2162d7aae91b1a43e07dfe5dddf73713d98eb7f3bb2a11229411c450f"],"state_sha256":"170c1ead652b60a661b9d17e6c3a1acb2684d4ae1f442a08518fb635cb265eba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O14JjMi4IVXwOKtBS1DQs6REToSY6hJgCD9ydhyk0F4N6K8Gpm74Uvji2YiYvqjjf62+XSScP5vlL96FAZvICg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-24T03:46:13.256799Z","bundle_sha256":"0dae3b5470d525ff39ef2342e9affd73454a3757996266bdb8002b6e5b54208f"}}