{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:E4FA4CVZKICPX3XZC67SH43HPB","short_pith_number":"pith:E4FA4CVZ","schema_version":"1.0","canonical_sha256":"270a0e0ab95204fbeef917bf23f3677844fa7e20776f72cbeba25ad1093c4e49","source":{"kind":"arxiv","id":"2108.09779","version":2},"attestation_state":"computed","paper":{"title":"Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.RO","authors_text":"Animesh Garg, Ankur Handa, Arthur Allshire, Denys Makoviichuk, Felix Widmaier, Manuel W\\\"uthrich, Mayank Mittal, Stefan Bauer, Varun Lodaya, Viktor Makoviychuk","submitted_at":"2021-08-22T16:45:58Z","abstract_excerpt":"We present a system for learning a challenging dexterous manipulation task involving moving a cube to an arbitrary 6-DoF pose with only 3-fingers trained with NVIDIA's IsaacGym simulator. We show empirical benefits, both in simulation and sim-to-real transfer, of using keypoints as opposed to position+quaternion representations for the object pose in 6-DoF for policy observations and in reward calculation to train a model-free reinforcement learning agent. By utilizing domain randomization strategies along with the keypoint representation of the pose of the manipulated object, we achieve a hig"},"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":"2108.09779","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2021-08-22T16:45:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e4366a7b9ef35dedf226f22ecc0771bd1e82c1acb42093b6158eb35031673875","abstract_canon_sha256":"6868c52455a469e4c0ba1d4ce00dc65c3581a9970cbef48165844854073d0ceb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:05.296847Z","signature_b64":"mCXdKOEIG/+MWZ+hL94q58UBivS1SAMg73vq9CAYOW0RyOzkB5GIptJ+mQ1IzM59wt+zVo30jZkrwkDq4B0ZCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"270a0e0ab95204fbeef917bf23f3677844fa7e20776f72cbeba25ad1093c4e49","last_reissued_at":"2026-07-05T07:53:05.296343Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:05.296343Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.RO","authors_text":"Animesh Garg, Ankur Handa, Arthur Allshire, Denys Makoviichuk, Felix Widmaier, Manuel W\\\"uthrich, Mayank Mittal, Stefan Bauer, Varun Lodaya, Viktor Makoviychuk","submitted_at":"2021-08-22T16:45:58Z","abstract_excerpt":"We present a system for learning a challenging dexterous manipulation task involving moving a cube to an arbitrary 6-DoF pose with only 3-fingers trained with NVIDIA's IsaacGym simulator. We show empirical benefits, both in simulation and sim-to-real transfer, of using keypoints as opposed to position+quaternion representations for the object pose in 6-DoF for policy observations and in reward calculation to train a model-free reinforcement learning agent. By utilizing domain randomization strategies along with the keypoint representation of the pose of the manipulated object, we achieve a hig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.09779","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2108.09779/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":"2108.09779","created_at":"2026-07-05T07:53:05.296404+00:00"},{"alias_kind":"arxiv_version","alias_value":"2108.09779v2","created_at":"2026-07-05T07:53:05.296404+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.09779","created_at":"2026-07-05T07:53:05.296404+00:00"},{"alias_kind":"pith_short_12","alias_value":"E4FA4CVZKICP","created_at":"2026-07-05T07:53:05.296404+00:00"},{"alias_kind":"pith_short_16","alias_value":"E4FA4CVZKICPX3XZ","created_at":"2026-07-05T07:53:05.296404+00:00"},{"alias_kind":"pith_short_8","alias_value":"E4FA4CVZ","created_at":"2026-07-05T07:53:05.296404+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/E4FA4CVZKICPX3XZC67SH43HPB","json":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB.json","graph_json":"https://pith.science/api/pith-number/E4FA4CVZKICPX3XZC67SH43HPB/graph.json","events_json":"https://pith.science/api/pith-number/E4FA4CVZKICPX3XZC67SH43HPB/events.json","paper":"https://pith.science/paper/E4FA4CVZ"},"agent_actions":{"view_html":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB","download_json":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB.json","view_paper":"https://pith.science/paper/E4FA4CVZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2108.09779&json=true","fetch_graph":"https://pith.science/api/pith-number/E4FA4CVZKICPX3XZC67SH43HPB/graph.json","fetch_events":"https://pith.science/api/pith-number/E4FA4CVZKICPX3XZC67SH43HPB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB/action/storage_attestation","attest_author":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB/action/author_attestation","sign_citation":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB/action/citation_signature","submit_replication":"https://pith.science/pith/E4FA4CVZKICPX3XZC67SH43HPB/action/replication_record"}},"created_at":"2026-07-05T07:53:05.296404+00:00","updated_at":"2026-07-05T07:53:05.296404+00:00"}