{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:7RIC46X3CNWCIQCGRU4YF444AB","short_pith_number":"pith:7RIC46X3","canonical_record":{"source":{"id":"2605.30468","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-28T18:40:52Z","cross_cats_sorted":[],"title_canon_sha256":"7a44549320b3fa247aea4c399123beb937c4de14e36d5881a4b6bbc2f2f431cd","abstract_canon_sha256":"290b27733d64a03201211ca811390ac5d1c97a777efe22ad30d6463295157eb5"},"schema_version":"1.0"},"canonical_sha256":"fc502e7afb136c2440468d3982f39c007755e39b4a1cbd712016c8ed854daf3a","source":{"kind":"arxiv","id":"2605.30468","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30468","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30468v1","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30468","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"pith_short_12","alias_value":"7RIC46X3CNWC","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"pith_short_16","alias_value":"7RIC46X3CNWCIQCG","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"pith_short_8","alias_value":"7RIC46X3","created_at":"2026-06-01T01:02:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:7RIC46X3CNWCIQCGRU4YF444AB","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30468","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-28T18:40:52Z","cross_cats_sorted":[],"title_canon_sha256":"7a44549320b3fa247aea4c399123beb937c4de14e36d5881a4b6bbc2f2f431cd","abstract_canon_sha256":"290b27733d64a03201211ca811390ac5d1c97a777efe22ad30d6463295157eb5"},"schema_version":"1.0"},"canonical_sha256":"fc502e7afb136c2440468d3982f39c007755e39b4a1cbd712016c8ed854daf3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:02:55.905519Z","signature_b64":"/Br0MGG4ple7Ina7UJacxcSvLZ2hFUS4WlXcZiA6MSvilCxiNLisw0Tv78SyAO1cD8HiBkHSBovqvXcHsksjCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc502e7afb136c2440468d3982f39c007755e39b4a1cbd712016c8ed854daf3a","last_reissued_at":"2026-06-01T01:02:55.904609Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:02:55.904609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30468","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":"2026-06-01T01:02:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"abfhyv9SLCNqV/DqKo62AjXxd36Qg2oaOuTDoN15nyFEaQXvWt28sqjZ5AlhKxSh5D5UrooVWWMTAXqVk+N4Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T09:51:06.925997Z"},"content_sha256":"2e306d3ed59b59a04d650b69b76f4e627c25af99edca55189defc22bd7ed5043","schema_version":"1.0","event_id":"sha256:2e306d3ed59b59a04d650b69b76f4e627c25af99edca55189defc22bd7ed5043"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:7RIC46X3CNWCIQCGRU4YF444AB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning-Based Navigation for Indoor Mobile Robots","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Gia-Uy Le, Tien-Dat Nguyen, Tri-Tin Nguyen, Vinh-Hao Nguyen, Vinh Nguyen","submitted_at":"2026-05-28T18:40:52Z","abstract_excerpt":"This paper presents a learning-based navigation framework for indoor mobile robots. The proposed method combines a supervised neural global planner, trained from cost-aware A* expert trajectories, with the proposed Learning-Based DWA local planner, which is formulated as discrete candidate selection over the Dynamic Window Approach (DWA) action lattice. For local planning, the policy is first trained by behavior cloning and then refined by Proximal Policy Optimization (PPO) under feasibility-aware masking. The framework is implemented and evaluated in both simulated and real-world indoor envir"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30468","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/2605.30468/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":"2026-06-01T01:02:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2ULqTBFjWpaURKIfgQprdkVa/t5xZMzQq81aAPuoJtHrJpmNRAMdLlVMBvS+FgV9tVbFzxgMXR/cFKY30XnoBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T09:51:06.926396Z"},"content_sha256":"edfe30a5f96e0d68e580d0c8e49391ff12ddb5243860a4a3e22798378b22c6af","schema_version":"1.0","event_id":"sha256:edfe30a5f96e0d68e580d0c8e49391ff12ddb5243860a4a3e22798378b22c6af"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7RIC46X3CNWCIQCGRU4YF444AB/bundle.json","state_url":"https://pith.science/pith/7RIC46X3CNWCIQCGRU4YF444AB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7RIC46X3CNWCIQCGRU4YF444AB/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":"2026-06-21T09:51:06Z","links":{"resolver":"https://pith.science/pith/7RIC46X3CNWCIQCGRU4YF444AB","bundle":"https://pith.science/pith/7RIC46X3CNWCIQCGRU4YF444AB/bundle.json","state":"https://pith.science/pith/7RIC46X3CNWCIQCGRU4YF444AB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7RIC46X3CNWCIQCGRU4YF444AB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7RIC46X3CNWCIQCGRU4YF444AB","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":"290b27733d64a03201211ca811390ac5d1c97a777efe22ad30d6463295157eb5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-28T18:40:52Z","title_canon_sha256":"7a44549320b3fa247aea4c399123beb937c4de14e36d5881a4b6bbc2f2f431cd"},"schema_version":"1.0","source":{"id":"2605.30468","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30468","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30468v1","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30468","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"pith_short_12","alias_value":"7RIC46X3CNWC","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"pith_short_16","alias_value":"7RIC46X3CNWCIQCG","created_at":"2026-06-01T01:02:55Z"},{"alias_kind":"pith_short_8","alias_value":"7RIC46X3","created_at":"2026-06-01T01:02:55Z"}],"graph_snapshots":[{"event_id":"sha256:edfe30a5f96e0d68e580d0c8e49391ff12ddb5243860a4a3e22798378b22c6af","target":"graph","created_at":"2026-06-01T01:02:55Z","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/2605.30468/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents a learning-based navigation framework for indoor mobile robots. The proposed method combines a supervised neural global planner, trained from cost-aware A* expert trajectories, with the proposed Learning-Based DWA local planner, which is formulated as discrete candidate selection over the Dynamic Window Approach (DWA) action lattice. For local planning, the policy is first trained by behavior cloning and then refined by Proximal Policy Optimization (PPO) under feasibility-aware masking. The framework is implemented and evaluated in both simulated and real-world indoor envir","authors_text":"Gia-Uy Le, Tien-Dat Nguyen, Tri-Tin Nguyen, Vinh-Hao Nguyen, Vinh Nguyen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-28T18:40:52Z","title":"Learning-Based Navigation for Indoor Mobile Robots"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30468","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":"sha256:2e306d3ed59b59a04d650b69b76f4e627c25af99edca55189defc22bd7ed5043","target":"record","created_at":"2026-06-01T01:02:55Z","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":"290b27733d64a03201211ca811390ac5d1c97a777efe22ad30d6463295157eb5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2026-05-28T18:40:52Z","title_canon_sha256":"7a44549320b3fa247aea4c399123beb937c4de14e36d5881a4b6bbc2f2f431cd"},"schema_version":"1.0","source":{"id":"2605.30468","kind":"arxiv","version":1}},"canonical_sha256":"fc502e7afb136c2440468d3982f39c007755e39b4a1cbd712016c8ed854daf3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc502e7afb136c2440468d3982f39c007755e39b4a1cbd712016c8ed854daf3a","first_computed_at":"2026-06-01T01:02:55.904609Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:02:55.904609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/Br0MGG4ple7Ina7UJacxcSvLZ2hFUS4WlXcZiA6MSvilCxiNLisw0Tv78SyAO1cD8HiBkHSBovqvXcHsksjCg==","signature_status":"signed_v1","signed_at":"2026-06-01T01:02:55.905519Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30468","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2e306d3ed59b59a04d650b69b76f4e627c25af99edca55189defc22bd7ed5043","sha256:edfe30a5f96e0d68e580d0c8e49391ff12ddb5243860a4a3e22798378b22c6af"],"state_sha256":"a5154261570629c0a18bcbfd074b175f4efa93bb4566a8160b2da58791e49147"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fawsr8bFDuKRvnVzS+i6d2seK9KXsDfvNSzhzIuAepco1AyMOacf5UAwVa8AI6Je8Js+iEzJw4zt/R3pXHn0AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T09:51:06.928429Z","bundle_sha256":"60311ba6ddc43a210d0c4f5cfd37cfd4f832e9f66f4a5348e7756a208712d5bd"}}