{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:IBCWR2Y3MRXVC2TA7IEBD74T34","short_pith_number":"pith:IBCWR2Y3","schema_version":"1.0","canonical_sha256":"404568eb1b646f516a60fa0811ff93df135b7fe5909c1ca48b3d0daf0a225563","source":{"kind":"arxiv","id":"2505.07532","version":1},"attestation_state":"computed","paper":{"title":"RAI: Flexible Agent Framework for Embodied AI","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.MA","authors_text":"Adam D\\k{a}browski, Bart{\\l}omiej Boczek, Kacper D\\k{a}browski, Kajetan Rachwa{\\l}, Maciej Majek, Maria Ganzha, Pawe{\\l} Liberadzki","submitted_at":"2025-05-12T13:13:47Z","abstract_excerpt":"With an increase in the capabilities of generative language models, a growing interest in embodied AI has followed. This contribution introduces RAI - a framework for creating embodied Multi Agent Systems for robotics. The proposed framework implements tools for Agents' integration with robotic stacks, Large Language Models, and simulations. It provides out-of-the-box integration with state-of-the-art systems like ROS 2. It also comes with dedicated mechanisms for the embodiment of Agents. These mechanisms have been tested on a physical robot, Husarion ROSBot XL, which was coupled with its dig"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.07532","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2025-05-12T13:13:47Z","cross_cats_sorted":[],"title_canon_sha256":"6fac42880ffd9e0b0266a63ba5f8e0abfa11078341dbb1dcbe2703f892294223","abstract_canon_sha256":"f4204bebe7926f346edd66f969a400a76d0d9c5477967b3eb2b4fecf5b82522b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:01:49.196201Z","signature_b64":"ebh9f6s881479LLP8rcGw16+2q1vDDFD8ZjlC6ge2eXOFFKDNbjSFNyb8kx9QUhHUaYhOoaFgnYVVLGcX208AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"404568eb1b646f516a60fa0811ff93df135b7fe5909c1ca48b3d0daf0a225563","last_reissued_at":"2026-07-05T11:01:49.195794Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:01:49.195794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RAI: Flexible Agent Framework for Embodied AI","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.MA","authors_text":"Adam D\\k{a}browski, Bart{\\l}omiej Boczek, Kacper D\\k{a}browski, Kajetan Rachwa{\\l}, Maciej Majek, Maria Ganzha, Pawe{\\l} Liberadzki","submitted_at":"2025-05-12T13:13:47Z","abstract_excerpt":"With an increase in the capabilities of generative language models, a growing interest in embodied AI has followed. This contribution introduces RAI - a framework for creating embodied Multi Agent Systems for robotics. The proposed framework implements tools for Agents' integration with robotic stacks, Large Language Models, and simulations. It provides out-of-the-box integration with state-of-the-art systems like ROS 2. It also comes with dedicated mechanisms for the embodiment of Agents. These mechanisms have been tested on a physical robot, Husarion ROSBot XL, which was coupled with its dig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.07532","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/2505.07532/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.07532","created_at":"2026-07-05T11:01:49.195853+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.07532v1","created_at":"2026-07-05T11:01:49.195853+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.07532","created_at":"2026-07-05T11:01:49.195853+00:00"},{"alias_kind":"pith_short_12","alias_value":"IBCWR2Y3MRXV","created_at":"2026-07-05T11:01:49.195853+00:00"},{"alias_kind":"pith_short_16","alias_value":"IBCWR2Y3MRXVC2TA","created_at":"2026-07-05T11:01:49.195853+00:00"},{"alias_kind":"pith_short_8","alias_value":"IBCWR2Y3","created_at":"2026-07-05T11:01:49.195853+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.09416","citing_title":"Harness Engineering for Physical AI: Robot Middleware Is the Harness Layer","ref_index":38,"is_internal_anchor":false},{"citing_arxiv_id":"2605.02525","citing_title":"A Semantic Autonomy Framework for VLM-Integrated Indoor Mobile Robots: Hybrid Deterministic Reasoning and Cross-Robot Adaptive Memory","ref_index":29,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34","json":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34.json","graph_json":"https://pith.science/api/pith-number/IBCWR2Y3MRXVC2TA7IEBD74T34/graph.json","events_json":"https://pith.science/api/pith-number/IBCWR2Y3MRXVC2TA7IEBD74T34/events.json","paper":"https://pith.science/paper/IBCWR2Y3"},"agent_actions":{"view_html":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34","download_json":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34.json","view_paper":"https://pith.science/paper/IBCWR2Y3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.07532&json=true","fetch_graph":"https://pith.science/api/pith-number/IBCWR2Y3MRXVC2TA7IEBD74T34/graph.json","fetch_events":"https://pith.science/api/pith-number/IBCWR2Y3MRXVC2TA7IEBD74T34/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34/action/storage_attestation","attest_author":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34/action/author_attestation","sign_citation":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34/action/citation_signature","submit_replication":"https://pith.science/pith/IBCWR2Y3MRXVC2TA7IEBD74T34/action/replication_record"}},"created_at":"2026-07-05T11:01:49.195853+00:00","updated_at":"2026-07-05T11:01:49.195853+00:00"}