{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VVLF4LYJZRA4FO5JRD64QGUISP","short_pith_number":"pith:VVLF4LYJ","canonical_record":{"source":{"id":"2504.13619","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-18T10:49:07Z","cross_cats_sorted":[],"title_canon_sha256":"5e6960cdf3e76b7023805802c2b63b8a87fb90cacc1ff699e1c1c8bb7e4f105e","abstract_canon_sha256":"3c61c800da2b03d8ecede15519bac686bebe83b774aebdc5d69d027a91963471"},"schema_version":"1.0"},"canonical_sha256":"ad565e2f09cc41c2bba988fdc81a8893fb59c9b147924f7fcead40a690613325","source":{"kind":"arxiv","id":"2504.13619","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.13619","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"arxiv_version","alias_value":"2504.13619v1","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.13619","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"pith_short_12","alias_value":"VVLF4LYJZRA4","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"pith_short_16","alias_value":"VVLF4LYJZRA4FO5J","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"pith_short_8","alias_value":"VVLF4LYJ","created_at":"2026-07-05T10:50:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VVLF4LYJZRA4FO5JRD64QGUISP","target":"record","payload":{"canonical_record":{"source":{"id":"2504.13619","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-18T10:49:07Z","cross_cats_sorted":[],"title_canon_sha256":"5e6960cdf3e76b7023805802c2b63b8a87fb90cacc1ff699e1c1c8bb7e4f105e","abstract_canon_sha256":"3c61c800da2b03d8ecede15519bac686bebe83b774aebdc5d69d027a91963471"},"schema_version":"1.0"},"canonical_sha256":"ad565e2f09cc41c2bba988fdc81a8893fb59c9b147924f7fcead40a690613325","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:50:59.177927Z","signature_b64":"We/pyciR0yecBN9YPCrleEW3AD1dyJbC6Ak2I/jaK8wcn/6k7GR+StoCupZfhhOElNyXsc1etBXyYaGPtbgRDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ad565e2f09cc41c2bba988fdc81a8893fb59c9b147924f7fcead40a690613325","last_reissued_at":"2026-07-05T10:50:59.177472Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:50:59.177472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.13619","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":"2026-07-05T10:50:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2O6UuDKlFW/dGkK8Dpd/RxCMiATG8qLhZKuj4PyydJ/XnnahpX08+ZtU2376vJ9iJ86RP/jygF8BQDl0gLtxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:11:29.104651Z"},"content_sha256":"03aca5e4efc53f7bf0fd3e8b6d19e4dfd3ac9e4f361cba9bbb478f2c03786806","schema_version":"1.0","event_id":"sha256:03aca5e4efc53f7bf0fd3e8b6d19e4dfd3ac9e4f361cba9bbb478f2c03786806"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VVLF4LYJZRA4FO5JRD64QGUISP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Fumio Kanehiro, Mehdi Benallegue, Mitsuharu Morisawa, Rohan P. Singh, Zhaoming Xie","submitted_at":"2025-04-18T10:49:07Z","abstract_excerpt":"For the deployment of legged robots in real-world environments, it is essential to develop robust locomotion control methods for challenging terrains that may exhibit unexpected deformability and irregularity. In this paper, we explore the application of sim-to-real deep reinforcement learning (RL) for the design of bipedal locomotion controllers for humanoid robots on compliant and uneven terrains. Our key contribution is to show that a simple training curriculum for exposing the RL agent to randomized terrains in simulation can achieve robust walking on a real humanoid robot using only propr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.13619","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/2504.13619/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":"2026-07-05T10:50:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tBQlMdqY7QgU2EODcdCcurgSwlY4/K2xGXL8gahdqfNko2hK9buXoqLpAIOVMSbdUdrJ9rLS+gZDl/zQvem6BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:11:29.105449Z"},"content_sha256":"c7d149967d43b295af83baa858aeba7c50f10b910ecb3f14e7eda26a99ad6403","schema_version":"1.0","event_id":"sha256:c7d149967d43b295af83baa858aeba7c50f10b910ecb3f14e7eda26a99ad6403"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VVLF4LYJZRA4FO5JRD64QGUISP/bundle.json","state_url":"https://pith.science/pith/VVLF4LYJZRA4FO5JRD64QGUISP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VVLF4LYJZRA4FO5JRD64QGUISP/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":"2026-08-04T15:11:29Z","links":{"resolver":"https://pith.science/pith/VVLF4LYJZRA4FO5JRD64QGUISP","bundle":"https://pith.science/pith/VVLF4LYJZRA4FO5JRD64QGUISP/bundle.json","state":"https://pith.science/pith/VVLF4LYJZRA4FO5JRD64QGUISP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VVLF4LYJZRA4FO5JRD64QGUISP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VVLF4LYJZRA4FO5JRD64QGUISP","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":"3c61c800da2b03d8ecede15519bac686bebe83b774aebdc5d69d027a91963471","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-18T10:49:07Z","title_canon_sha256":"5e6960cdf3e76b7023805802c2b63b8a87fb90cacc1ff699e1c1c8bb7e4f105e"},"schema_version":"1.0","source":{"id":"2504.13619","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.13619","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"arxiv_version","alias_value":"2504.13619v1","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.13619","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"pith_short_12","alias_value":"VVLF4LYJZRA4","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"pith_short_16","alias_value":"VVLF4LYJZRA4FO5J","created_at":"2026-07-05T10:50:59Z"},{"alias_kind":"pith_short_8","alias_value":"VVLF4LYJ","created_at":"2026-07-05T10:50:59Z"}],"graph_snapshots":[{"event_id":"sha256:c7d149967d43b295af83baa858aeba7c50f10b910ecb3f14e7eda26a99ad6403","target":"graph","created_at":"2026-07-05T10:50:59Z","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/2504.13619/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"For the deployment of legged robots in real-world environments, it is essential to develop robust locomotion control methods for challenging terrains that may exhibit unexpected deformability and irregularity. In this paper, we explore the application of sim-to-real deep reinforcement learning (RL) for the design of bipedal locomotion controllers for humanoid robots on compliant and uneven terrains. Our key contribution is to show that a simple training curriculum for exposing the RL agent to randomized terrains in simulation can achieve robust walking on a real humanoid robot using only propr","authors_text":"Fumio Kanehiro, Mehdi Benallegue, Mitsuharu Morisawa, Rohan P. Singh, Zhaoming Xie","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-18T10:49:07Z","title":"Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.13619","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":"sha256:03aca5e4efc53f7bf0fd3e8b6d19e4dfd3ac9e4f361cba9bbb478f2c03786806","target":"record","created_at":"2026-07-05T10:50:59Z","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":"3c61c800da2b03d8ecede15519bac686bebe83b774aebdc5d69d027a91963471","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-18T10:49:07Z","title_canon_sha256":"5e6960cdf3e76b7023805802c2b63b8a87fb90cacc1ff699e1c1c8bb7e4f105e"},"schema_version":"1.0","source":{"id":"2504.13619","kind":"arxiv","version":1}},"canonical_sha256":"ad565e2f09cc41c2bba988fdc81a8893fb59c9b147924f7fcead40a690613325","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ad565e2f09cc41c2bba988fdc81a8893fb59c9b147924f7fcead40a690613325","first_computed_at":"2026-07-05T10:50:59.177472Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:50:59.177472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"We/pyciR0yecBN9YPCrleEW3AD1dyJbC6Ak2I/jaK8wcn/6k7GR+StoCupZfhhOElNyXsc1etBXyYaGPtbgRDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:50:59.177927Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.13619","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:03aca5e4efc53f7bf0fd3e8b6d19e4dfd3ac9e4f361cba9bbb478f2c03786806","sha256:c7d149967d43b295af83baa858aeba7c50f10b910ecb3f14e7eda26a99ad6403"],"state_sha256":"1a0c293fd9361c32aeabfbc98b190da4d5a2ad73d04c652a0b67800a75204f59"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"10RESlELs2a/J0nsRusUA01OA4XqyHLvo7Q/G+yxXbxnXYvq+Yox4I2VhhgXpWjLda4PK48TZtztHrbI5PZQBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T15:11:29.115921Z","bundle_sha256":"299ca08e04a100937ad92b88dcb581238a8a25186f399bb5e7c287fddf27d878"}}