{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:QFO6MZ2UYRFWLVUYKHO7RHW4EN","short_pith_number":"pith:QFO6MZ2U","schema_version":"1.0","canonical_sha256":"815de66754c44b65d69851ddf89edc237534a410c28a619454566ac945cffc45","source":{"kind":"arxiv","id":"1906.11114","version":1},"attestation_state":"computed","paper":{"title":"From Multi-modal Property Dataset to Robot-centric Conceptual Knowledge About Household Objects","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.AI","authors_text":"Andreas Birk, Christian A. Mueller, Georg Jaeger, Johannes Schleiss, Madhura Thosar, Max Pfingsthorn, Narender Pulugu, Ravi Mallikarjun Chennaboina, Sai Vivek Jeevangekar, Sebastian Zug","submitted_at":"2019-06-26T14:11:41Z","abstract_excerpt":"Tool-use applications in robotics require conceptual knowledge about objects for informed decision making and object interactions. State-of-the-art methods employ hand-crafted symbolic knowledge which is defined from a human perspective and grounded into sensory data afterwards. However, due to different sensing and acting capabilities of robots, their conceptual understanding of objects must be generated from a robot's perspective entirely, which asks for robot-centric conceptual knowledge about objects. With this goal in mind, this article motivates that such knowledge should be based on phy"},"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":"1906.11114","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-06-26T14:11:41Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"316711d446968d60c2a666ccc77ac07a1874d0ef8f46d8a91b06bb9c8c5577dc","abstract_canon_sha256":"4c8df868effcf022c91f98544410dce30fc73617ed0bfd2335110798048de908"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:09.773037Z","signature_b64":"EioM036nDI+NRVJ9t5HXkRAexxQtxAcxN30117Uq1xU++slSdxnZpU1RSol+UHb7cAnxOW2/Ml+KPGRfLacZAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"815de66754c44b65d69851ddf89edc237534a410c28a619454566ac945cffc45","last_reissued_at":"2026-05-17T23:42:09.772340Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:09.772340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"From Multi-modal Property Dataset to Robot-centric Conceptual Knowledge About Household Objects","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.AI","authors_text":"Andreas Birk, Christian A. Mueller, Georg Jaeger, Johannes Schleiss, Madhura Thosar, Max Pfingsthorn, Narender Pulugu, Ravi Mallikarjun Chennaboina, Sai Vivek Jeevangekar, Sebastian Zug","submitted_at":"2019-06-26T14:11:41Z","abstract_excerpt":"Tool-use applications in robotics require conceptual knowledge about objects for informed decision making and object interactions. State-of-the-art methods employ hand-crafted symbolic knowledge which is defined from a human perspective and grounded into sensory data afterwards. However, due to different sensing and acting capabilities of robots, their conceptual understanding of objects must be generated from a robot's perspective entirely, which asks for robot-centric conceptual knowledge about objects. With this goal in mind, this article motivates that such knowledge should be based on phy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11114","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":""},"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":"1906.11114","created_at":"2026-05-17T23:42:09.772455+00:00"},{"alias_kind":"arxiv_version","alias_value":"1906.11114v1","created_at":"2026-05-17T23:42:09.772455+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11114","created_at":"2026-05-17T23:42:09.772455+00:00"},{"alias_kind":"pith_short_12","alias_value":"QFO6MZ2UYRFW","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_16","alias_value":"QFO6MZ2UYRFWLVUY","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_8","alias_value":"QFO6MZ2U","created_at":"2026-05-18T12:33:27.125529+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN","json":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN.json","graph_json":"https://pith.science/api/pith-number/QFO6MZ2UYRFWLVUYKHO7RHW4EN/graph.json","events_json":"https://pith.science/api/pith-number/QFO6MZ2UYRFWLVUYKHO7RHW4EN/events.json","paper":"https://pith.science/paper/QFO6MZ2U"},"agent_actions":{"view_html":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN","download_json":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN.json","view_paper":"https://pith.science/paper/QFO6MZ2U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1906.11114&json=true","fetch_graph":"https://pith.science/api/pith-number/QFO6MZ2UYRFWLVUYKHO7RHW4EN/graph.json","fetch_events":"https://pith.science/api/pith-number/QFO6MZ2UYRFWLVUYKHO7RHW4EN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN/action/storage_attestation","attest_author":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN/action/author_attestation","sign_citation":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN/action/citation_signature","submit_replication":"https://pith.science/pith/QFO6MZ2UYRFWLVUYKHO7RHW4EN/action/replication_record"}},"created_at":"2026-05-17T23:42:09.772455+00:00","updated_at":"2026-05-17T23:42:09.772455+00:00"}