{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:XTVXZFFHAOJNBDZCZT7JQBVJXD","short_pith_number":"pith:XTVXZFFH","schema_version":"1.0","canonical_sha256":"bceb7c94a70392d08f22ccfe9806a9b8e8308b649fe004cab678fa403999d308","source":{"kind":"arxiv","id":"1707.01696","version":2},"attestation_state":"computed","paper":{"title":"Generalized Task-Parameterized Skill Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Darwin G. Caldwell, Jo\\~ao Silv\\'erio, Leonel Rozo, Yanlong Huang","submitted_at":"2017-07-06T09:08:08Z","abstract_excerpt":"Programming by demonstration has recently gained much attention due to its user-friendly and natural way to transfer human skills to robots. In order to facilitate the learning of multiple demonstrations and meanwhile generalize to new situations, a task-parameterized Gaussian mixture model (TP-GMM) has been recently developed. This model has achieved reliable performance in areas such as human-robot collaboration and dual-arm manipulation. However, the crucial task frames and associated parameters in this learning framework are often set by the human teacher, which renders three problems that"},"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":"1707.01696","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2017-07-06T09:08:08Z","cross_cats_sorted":[],"title_canon_sha256":"0f2115f53a0a7b5fc760e46d8c261a583c1bb6df43790981e9e81faa246a27e6","abstract_canon_sha256":"8db8ab03dd3729622760e4161c11a3406c7885f6bb38435ce3bfef4ea9cf83b5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:05.992601Z","signature_b64":"78/pOm9GzSJG+07sCJjAy35Te2Rh/OX13hZZuPbyKiCm/CV77Pqq0Fu5cMVMkiFM3t15vu7lIh3nIYs0pLySCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bceb7c94a70392d08f22ccfe9806a9b8e8308b649fe004cab678fa403999d308","last_reissued_at":"2026-05-18T00:22:05.992117Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:05.992117Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generalized Task-Parameterized Skill Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Darwin G. Caldwell, Jo\\~ao Silv\\'erio, Leonel Rozo, Yanlong Huang","submitted_at":"2017-07-06T09:08:08Z","abstract_excerpt":"Programming by demonstration has recently gained much attention due to its user-friendly and natural way to transfer human skills to robots. In order to facilitate the learning of multiple demonstrations and meanwhile generalize to new situations, a task-parameterized Gaussian mixture model (TP-GMM) has been recently developed. This model has achieved reliable performance in areas such as human-robot collaboration and dual-arm manipulation. However, the crucial task frames and associated parameters in this learning framework are often set by the human teacher, which renders three problems that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.01696","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":""},"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":"1707.01696","created_at":"2026-05-18T00:22:05.992191+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.01696v2","created_at":"2026-05-18T00:22:05.992191+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.01696","created_at":"2026-05-18T00:22:05.992191+00:00"},{"alias_kind":"pith_short_12","alias_value":"XTVXZFFHAOJN","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"XTVXZFFHAOJNBDZC","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"XTVXZFFH","created_at":"2026-05-18T12:31:56.362134+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/XTVXZFFHAOJNBDZCZT7JQBVJXD","json":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD.json","graph_json":"https://pith.science/api/pith-number/XTVXZFFHAOJNBDZCZT7JQBVJXD/graph.json","events_json":"https://pith.science/api/pith-number/XTVXZFFHAOJNBDZCZT7JQBVJXD/events.json","paper":"https://pith.science/paper/XTVXZFFH"},"agent_actions":{"view_html":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD","download_json":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD.json","view_paper":"https://pith.science/paper/XTVXZFFH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.01696&json=true","fetch_graph":"https://pith.science/api/pith-number/XTVXZFFHAOJNBDZCZT7JQBVJXD/graph.json","fetch_events":"https://pith.science/api/pith-number/XTVXZFFHAOJNBDZCZT7JQBVJXD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD/action/storage_attestation","attest_author":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD/action/author_attestation","sign_citation":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD/action/citation_signature","submit_replication":"https://pith.science/pith/XTVXZFFHAOJNBDZCZT7JQBVJXD/action/replication_record"}},"created_at":"2026-05-18T00:22:05.992191+00:00","updated_at":"2026-05-18T00:22:05.992191+00:00"}