{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:VYTYDPYH2BP7FZ5MGO472W4KZ3","short_pith_number":"pith:VYTYDPYH","schema_version":"1.0","canonical_sha256":"ae2781bf07d05ff2e7ac33b9fd5b8acedc9316fcf2f4da626e0809be2e583641","source":{"kind":"arxiv","id":"1803.07635","version":2},"attestation_state":"computed","paper":{"title":"Learning Robotic Assembly from CAD","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.RO","authors_text":"Aviv Tamar, Garrett Thomas, Juan Aparicio Ojea, Melissa Chien, Pieter Abbeel","submitted_at":"2018-03-20T20:16:18Z","abstract_excerpt":"In this work, motivated by recent manufacturing trends, we investigate autonomous robotic assembly. Industrial assembly tasks require contact-rich manipulation skills, which are challenging to acquire using classical control and motion planning approaches. Consequently, robot controllers for assembly domains are presently engineered to solve a particular task, and cannot easily handle variations in the product or environment. Reinforcement learning (RL) is a promising approach for autonomously acquiring robot skills that involve contact-rich dynamics. However, RL relies on random exploration f"},"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":"1803.07635","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-03-20T20:16:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"13cdedeb2cd6a7d0def354f5dff33c8c471061915353983fe29aa24d72fb1e92","abstract_canon_sha256":"7cf2bd2c2e4f4ea69475f9e1b53086231e255fb46eba56258ee5c5334ae3d9a3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:52.489729Z","signature_b64":"uwieCo3nfYEX/HdryO3teH+wb1iqdUI0Qt1wykfF8TJDXo4EGxosSVo9QDWBnxHyXAq3SNcgYR/9Kr0pBlMUBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae2781bf07d05ff2e7ac33b9fd5b8acedc9316fcf2f4da626e0809be2e583641","last_reissued_at":"2026-05-18T00:09:52.489221Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:52.489221Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Robotic Assembly from CAD","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.RO","authors_text":"Aviv Tamar, Garrett Thomas, Juan Aparicio Ojea, Melissa Chien, Pieter Abbeel","submitted_at":"2018-03-20T20:16:18Z","abstract_excerpt":"In this work, motivated by recent manufacturing trends, we investigate autonomous robotic assembly. Industrial assembly tasks require contact-rich manipulation skills, which are challenging to acquire using classical control and motion planning approaches. Consequently, robot controllers for assembly domains are presently engineered to solve a particular task, and cannot easily handle variations in the product or environment. Reinforcement learning (RL) is a promising approach for autonomously acquiring robot skills that involve contact-rich dynamics. However, RL relies on random exploration f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.07635","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":"1803.07635","created_at":"2026-05-18T00:09:52.489300+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.07635v2","created_at":"2026-05-18T00:09:52.489300+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.07635","created_at":"2026-05-18T00:09:52.489300+00:00"},{"alias_kind":"pith_short_12","alias_value":"VYTYDPYH2BP7","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_16","alias_value":"VYTYDPYH2BP7FZ5M","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_8","alias_value":"VYTYDPYH","created_at":"2026-05-18T12:32:59.047623+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/VYTYDPYH2BP7FZ5MGO472W4KZ3","json":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3.json","graph_json":"https://pith.science/api/pith-number/VYTYDPYH2BP7FZ5MGO472W4KZ3/graph.json","events_json":"https://pith.science/api/pith-number/VYTYDPYH2BP7FZ5MGO472W4KZ3/events.json","paper":"https://pith.science/paper/VYTYDPYH"},"agent_actions":{"view_html":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3","download_json":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3.json","view_paper":"https://pith.science/paper/VYTYDPYH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.07635&json=true","fetch_graph":"https://pith.science/api/pith-number/VYTYDPYH2BP7FZ5MGO472W4KZ3/graph.json","fetch_events":"https://pith.science/api/pith-number/VYTYDPYH2BP7FZ5MGO472W4KZ3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3/action/storage_attestation","attest_author":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3/action/author_attestation","sign_citation":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3/action/citation_signature","submit_replication":"https://pith.science/pith/VYTYDPYH2BP7FZ5MGO472W4KZ3/action/replication_record"}},"created_at":"2026-05-18T00:09:52.489300+00:00","updated_at":"2026-05-18T00:09:52.489300+00:00"}