{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5BXJHBJ2ACLAHRM4WVRYVGJOIU","short_pith_number":"pith:5BXJHBJ2","canonical_record":{"source":{"id":"2507.16233","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-22T05:07:11Z","cross_cats_sorted":[],"title_canon_sha256":"67ac1b3695ad85d8ce0c7bc79ee1d5068feefa313530f89c9327d21838b09e0e","abstract_canon_sha256":"ccdc28509215bb5ae64ad57031595c8e6a43f891c042cbcfb4997c20386b0b7e"},"schema_version":"1.0"},"canonical_sha256":"e86e93853a009603c59cb5638a992e453d82f6ae9093c08c1c63c40b86f9db3b","source":{"kind":"arxiv","id":"2507.16233","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.16233","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"2507.16233v1","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.16233","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"5BXJHBJ2ACLA","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"pith_short_16","alias_value":"5BXJHBJ2ACLAHRM4","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"pith_short_8","alias_value":"5BXJHBJ2","created_at":"2026-07-05T11:41:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5BXJHBJ2ACLAHRM4WVRYVGJOIU","target":"record","payload":{"canonical_record":{"source":{"id":"2507.16233","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-22T05:07:11Z","cross_cats_sorted":[],"title_canon_sha256":"67ac1b3695ad85d8ce0c7bc79ee1d5068feefa313530f89c9327d21838b09e0e","abstract_canon_sha256":"ccdc28509215bb5ae64ad57031595c8e6a43f891c042cbcfb4997c20386b0b7e"},"schema_version":"1.0"},"canonical_sha256":"e86e93853a009603c59cb5638a992e453d82f6ae9093c08c1c63c40b86f9db3b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:41:06.031473Z","signature_b64":"0weBQzD71DdOkxlCSPhfpfy9SWDeJszgfFB+LhEA8N+DfLdha7PKvZe+AF8vry5ymU7yvvZ1ddTzExbSIw8FCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e86e93853a009603c59cb5638a992e453d82f6ae9093c08c1c63c40b86f9db3b","last_reissued_at":"2026-07-05T11:41:06.030657Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:41:06.030657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.16233","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":"2026-07-05T11:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9+cc3ddvAmaG91leIIFM3m931x2Wrzno9HBDAUZF+ir/6y0z9t8WIBp2DyFrevK2YB6Gs4OW5dbOGxyvrqYXAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T01:44:03.395696Z"},"content_sha256":"48d1c2e95a951f103225e72f2df72398197750e73981eb8fb9b25fd8cda4611a","schema_version":"1.0","event_id":"sha256:48d1c2e95a951f103225e72f2df72398197750e73981eb8fb9b25fd8cda4611a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5BXJHBJ2ACLAHRM4WVRYVGJOIU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GFM-Planner: Perception-Aware Trajectory Planning with Geometric Feature Metric","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Dong Wang, Huchuan Lu, Xiaoxuan Zhang, Yang Liu, Yue Lin","submitted_at":"2025-07-22T05:07:11Z","abstract_excerpt":"Like humans who rely on landmarks for orientation, autonomous robots depend on feature-rich environments for accurate localization. In this paper, we propose the GFM-Planner, a perception-aware trajectory planning framework based on the geometric feature metric, which enhances LiDAR localization accuracy by guiding the robot to avoid degraded areas. First, we derive the Geometric Feature Metric (GFM) from the fundamental LiDAR localization problem. Next, we design a 2D grid-based Metric Encoding Map (MEM) to efficiently store GFM values across the environment. A constant-time decoding algorith"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.16233","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/2507.16233/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":"2026-07-05T11:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GL12wEAyjK5n2fQs12UAb5MjQOFpZ9iDLNQblU6aQ2W3isijth2IyGhMXLgGwNtVXPNwEYMCbv1Kr7ZrJ3bYAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T01:44:03.396184Z"},"content_sha256":"8c0645df107302c428d6ccb9f79cf2b71c5fd4cb579288745c99d1805d01302c","schema_version":"1.0","event_id":"sha256:8c0645df107302c428d6ccb9f79cf2b71c5fd4cb579288745c99d1805d01302c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU/bundle.json","state_url":"https://pith.science/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU/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":"2026-08-06T01:44:03Z","links":{"resolver":"https://pith.science/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU","bundle":"https://pith.science/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU/bundle.json","state":"https://pith.science/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5BXJHBJ2ACLAHRM4WVRYVGJOIU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5BXJHBJ2ACLAHRM4WVRYVGJOIU","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":"ccdc28509215bb5ae64ad57031595c8e6a43f891c042cbcfb4997c20386b0b7e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-22T05:07:11Z","title_canon_sha256":"67ac1b3695ad85d8ce0c7bc79ee1d5068feefa313530f89c9327d21838b09e0e"},"schema_version":"1.0","source":{"id":"2507.16233","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.16233","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"2507.16233v1","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.16233","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"5BXJHBJ2ACLA","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"pith_short_16","alias_value":"5BXJHBJ2ACLAHRM4","created_at":"2026-07-05T11:41:06Z"},{"alias_kind":"pith_short_8","alias_value":"5BXJHBJ2","created_at":"2026-07-05T11:41:06Z"}],"graph_snapshots":[{"event_id":"sha256:8c0645df107302c428d6ccb9f79cf2b71c5fd4cb579288745c99d1805d01302c","target":"graph","created_at":"2026-07-05T11:41:06Z","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/2507.16233/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Like humans who rely on landmarks for orientation, autonomous robots depend on feature-rich environments for accurate localization. In this paper, we propose the GFM-Planner, a perception-aware trajectory planning framework based on the geometric feature metric, which enhances LiDAR localization accuracy by guiding the robot to avoid degraded areas. First, we derive the Geometric Feature Metric (GFM) from the fundamental LiDAR localization problem. Next, we design a 2D grid-based Metric Encoding Map (MEM) to efficiently store GFM values across the environment. A constant-time decoding algorith","authors_text":"Dong Wang, Huchuan Lu, Xiaoxuan Zhang, Yang Liu, Yue Lin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-22T05:07:11Z","title":"GFM-Planner: Perception-Aware Trajectory Planning with Geometric Feature Metric"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.16233","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":"sha256:48d1c2e95a951f103225e72f2df72398197750e73981eb8fb9b25fd8cda4611a","target":"record","created_at":"2026-07-05T11:41:06Z","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":"ccdc28509215bb5ae64ad57031595c8e6a43f891c042cbcfb4997c20386b0b7e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-22T05:07:11Z","title_canon_sha256":"67ac1b3695ad85d8ce0c7bc79ee1d5068feefa313530f89c9327d21838b09e0e"},"schema_version":"1.0","source":{"id":"2507.16233","kind":"arxiv","version":1}},"canonical_sha256":"e86e93853a009603c59cb5638a992e453d82f6ae9093c08c1c63c40b86f9db3b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e86e93853a009603c59cb5638a992e453d82f6ae9093c08c1c63c40b86f9db3b","first_computed_at":"2026-07-05T11:41:06.030657Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:41:06.030657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0weBQzD71DdOkxlCSPhfpfy9SWDeJszgfFB+LhEA8N+DfLdha7PKvZe+AF8vry5ymU7yvvZ1ddTzExbSIw8FCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:41:06.031473Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.16233","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48d1c2e95a951f103225e72f2df72398197750e73981eb8fb9b25fd8cda4611a","sha256:8c0645df107302c428d6ccb9f79cf2b71c5fd4cb579288745c99d1805d01302c"],"state_sha256":"1018601937424b3525ef93f3cad36e34520ef3613fb3e3752d27417114a45109"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DEH097psB3z8ynlpXzfhLci6OtGiaNPMsRaP3Bv2FPbN8uxaJ4sKMxj6ci/BZTzP/3DcJzYo9u8eLnubd+h1CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T01:44:03.399794Z","bundle_sha256":"af9f0fb9399aab87229afe1d7dfab7dbd57a7e37c8d591178fb809412caed538"}}