{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:LXG35K6YP6X5RO3E7RPFIURVO5","short_pith_number":"pith:LXG35K6Y","canonical_record":{"source":{"id":"2404.03094","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-04-03T22:16:49Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"964011a8a8c08be214b8d9cd1cae3988fd360836cbb4816faaefc90d43e2c254","abstract_canon_sha256":"3d503e73a905c0054bf6b99d26ac0ac2b1713c92e0e1f09dcf9aab1bb7643232"},"schema_version":"1.0"},"canonical_sha256":"5dcdbeabd87fafd8bb64fc5e545235776a9c5d9b6ba3b46f5746bcff5166b589","source":{"kind":"arxiv","id":"2404.03094","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.03094","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"arxiv_version","alias_value":"2404.03094v2","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.03094","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"pith_short_12","alias_value":"LXG35K6YP6X5","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"pith_short_16","alias_value":"LXG35K6YP6X5RO3E","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"pith_short_8","alias_value":"LXG35K6Y","created_at":"2026-07-05T10:27:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:LXG35K6YP6X5RO3E7RPFIURVO5","target":"record","payload":{"canonical_record":{"source":{"id":"2404.03094","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-04-03T22:16:49Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"964011a8a8c08be214b8d9cd1cae3988fd360836cbb4816faaefc90d43e2c254","abstract_canon_sha256":"3d503e73a905c0054bf6b99d26ac0ac2b1713c92e0e1f09dcf9aab1bb7643232"},"schema_version":"1.0"},"canonical_sha256":"5dcdbeabd87fafd8bb64fc5e545235776a9c5d9b6ba3b46f5746bcff5166b589","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:27:08.967370Z","signature_b64":"EdfGNzgXxB9ZQKzXsfVBsJ4VTMi3gjycgQVPseZN0bePzam8CN9v5443kOtyPDD9yerBY2xftS2pvTgiV6kWDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5dcdbeabd87fafd8bb64fc5e545235776a9c5d9b6ba3b46f5746bcff5166b589","last_reissued_at":"2026-07-05T10:27:08.966457Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:27:08.966457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.03094","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:27:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GKGLMK1SZmYR7OaAPPICIHZbwNRneHPY/Gh5tyDNn38elNFsAjMxzaJ3ZtZSbQ5SA9SEpQ7AOjHdMVtx4lUDBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T12:37:41.367532Z"},"content_sha256":"e809d958c1b0187f83432f727b5ea6ef74ac213c0b53eb0047ee675322244646","schema_version":"1.0","event_id":"sha256:e809d958c1b0187f83432f727b5ea6ef74ac213c0b53eb0047ee675322244646"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:LXG35K6YP6X5RO3E7RPFIURVO5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Low Frequency Sampling in Model Predictive Path Integral Control","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.RO","authors_text":"Ali-akbar Agha-mohammadi, Bogdan Vlahov, David D. Fan, Evangelos A. Theodorou, Jason Gibson, Patrick Spieler","submitted_at":"2024-04-03T22:16:49Z","abstract_excerpt":"Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show how the default choice of uncorrelated Gaussian distributions can be improved upon with the use of a colored noise distribution. Our choice of distribution allows for the emphasis on low frequency control signals, which can result in smoother and more exploratory samples. We use this frequency-based sampling distribution with Model Predictive Path Integral (MPPI) in both hardware and simulation experiments to show bet"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.03094","kind":"arxiv","version":2},"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/2404.03094/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":"2026-07-05T10:27:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F4iz7FolMQj7+SnPG15+pJORtDbGNbyae0pczvPzQYxyUv+6Tmwawkbtc1A2WeZMfcXzWiGXZFqEJBb5M8vwAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T12:37:41.367905Z"},"content_sha256":"2a1bd69b01237f91c4503b5dbb4204bdb73d14eaa020e488edc13abdea4134f9","schema_version":"1.0","event_id":"sha256:2a1bd69b01237f91c4503b5dbb4204bdb73d14eaa020e488edc13abdea4134f9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LXG35K6YP6X5RO3E7RPFIURVO5/bundle.json","state_url":"https://pith.science/pith/LXG35K6YP6X5RO3E7RPFIURVO5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LXG35K6YP6X5RO3E7RPFIURVO5/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":"2026-07-07T12:37:41Z","links":{"resolver":"https://pith.science/pith/LXG35K6YP6X5RO3E7RPFIURVO5","bundle":"https://pith.science/pith/LXG35K6YP6X5RO3E7RPFIURVO5/bundle.json","state":"https://pith.science/pith/LXG35K6YP6X5RO3E7RPFIURVO5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LXG35K6YP6X5RO3E7RPFIURVO5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LXG35K6YP6X5RO3E7RPFIURVO5","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":"3d503e73a905c0054bf6b99d26ac0ac2b1713c92e0e1f09dcf9aab1bb7643232","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-04-03T22:16:49Z","title_canon_sha256":"964011a8a8c08be214b8d9cd1cae3988fd360836cbb4816faaefc90d43e2c254"},"schema_version":"1.0","source":{"id":"2404.03094","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.03094","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"arxiv_version","alias_value":"2404.03094v2","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.03094","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"pith_short_12","alias_value":"LXG35K6YP6X5","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"pith_short_16","alias_value":"LXG35K6YP6X5RO3E","created_at":"2026-07-05T10:27:08Z"},{"alias_kind":"pith_short_8","alias_value":"LXG35K6Y","created_at":"2026-07-05T10:27:08Z"}],"graph_snapshots":[{"event_id":"sha256:2a1bd69b01237f91c4503b5dbb4204bdb73d14eaa020e488edc13abdea4134f9","target":"graph","created_at":"2026-07-05T10:27:08Z","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/2404.03094/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show how the default choice of uncorrelated Gaussian distributions can be improved upon with the use of a colored noise distribution. Our choice of distribution allows for the emphasis on low frequency control signals, which can result in smoother and more exploratory samples. We use this frequency-based sampling distribution with Model Predictive Path Integral (MPPI) in both hardware and simulation experiments to show bet","authors_text":"Ali-akbar Agha-mohammadi, Bogdan Vlahov, David D. Fan, Evangelos A. Theodorou, Jason Gibson, Patrick Spieler","cross_cats":["math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-04-03T22:16:49Z","title":"Low Frequency Sampling in Model Predictive Path Integral Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.03094","kind":"arxiv","version":2},"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:e809d958c1b0187f83432f727b5ea6ef74ac213c0b53eb0047ee675322244646","target":"record","created_at":"2026-07-05T10:27:08Z","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":"3d503e73a905c0054bf6b99d26ac0ac2b1713c92e0e1f09dcf9aab1bb7643232","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-04-03T22:16:49Z","title_canon_sha256":"964011a8a8c08be214b8d9cd1cae3988fd360836cbb4816faaefc90d43e2c254"},"schema_version":"1.0","source":{"id":"2404.03094","kind":"arxiv","version":2}},"canonical_sha256":"5dcdbeabd87fafd8bb64fc5e545235776a9c5d9b6ba3b46f5746bcff5166b589","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5dcdbeabd87fafd8bb64fc5e545235776a9c5d9b6ba3b46f5746bcff5166b589","first_computed_at":"2026-07-05T10:27:08.966457Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:27:08.966457Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EdfGNzgXxB9ZQKzXsfVBsJ4VTMi3gjycgQVPseZN0bePzam8CN9v5443kOtyPDD9yerBY2xftS2pvTgiV6kWDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:27:08.967370Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.03094","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e809d958c1b0187f83432f727b5ea6ef74ac213c0b53eb0047ee675322244646","sha256:2a1bd69b01237f91c4503b5dbb4204bdb73d14eaa020e488edc13abdea4134f9"],"state_sha256":"e3f4cfde1cf591faba1286c99613a85aa4307c3e86f4226e662c3428559afd50"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c5ZslZv9B6xB9h21Nv6uWNlhWhWClY/C8FEWWm4wBxKhtTOCZ1QjZzUmZ1lDNmSy9HOUpIXHDtS7FzTFQo8qDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T12:37:41.370795Z","bundle_sha256":"75d308077415d1b60742aafa125beef76af36846a953bbce5058e640841dc23f"}}