{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:CPBS3KETDPTYFAK4QE3I6CQKYN","short_pith_number":"pith:CPBS3KET","schema_version":"1.0","canonical_sha256":"13c32da8931be782815c81368f0a0ac3453918f4bdb183015b7a4f92fc1aada7","source":{"kind":"arxiv","id":"2502.07380","version":2},"attestation_state":"computed","paper":{"title":"Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Bhaumik Mehta, Bryan Xu, Byron Boots, Emma Romig, Gabriel Guo, Preet Shah, Rosario Scalise, Sanghun Jung, Sidharth Rajagopal, Sidharth Talia, Tyler Han, Yanda Bao","submitted_at":"2025-02-11T08:57:41Z","abstract_excerpt":"Reinforcement Learning (RL) has been pivotal in recent robotics milestones and is poised to play a prominent role in the future. However, these advances can rely on proprietary simulators, expensive hardware, and a daunting range of tools and skills. As a result, broader communities are disconnecting from the state-of-the-art; education curricula are poorly equipped to teach indispensable modern robotics skills involving hardware, deployment, and iterative development. To address this gap between the broader and scientific communities, we contribute Wheeled Lab, an ecosystem which integrates a"},"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":"2502.07380","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-02-11T08:57:41Z","cross_cats_sorted":[],"title_canon_sha256":"ec59a55eabbf57f0e6030fcb6ccbbbbbf89547cc18bb74c1fc123e5110911805","abstract_canon_sha256":"3adcaf1a3464b89af38d555a9a7b47d9a320449164fad117c2fe2f551dd8628b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:01:57.439938Z","signature_b64":"QXHa3SgW8qyb+i63K/ZcKOJKhyS6Mq6MTx9lhxe2vQ4pd/JX86ETRP+3rzm4/dRWAYb26//wi002D/pVvkzXCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"13c32da8931be782815c81368f0a0ac3453918f4bdb183015b7a4f92fc1aada7","last_reissued_at":"2026-07-05T12:01:57.439416Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:01:57.439416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Bhaumik Mehta, Bryan Xu, Byron Boots, Emma Romig, Gabriel Guo, Preet Shah, Rosario Scalise, Sanghun Jung, Sidharth Rajagopal, Sidharth Talia, Tyler Han, Yanda Bao","submitted_at":"2025-02-11T08:57:41Z","abstract_excerpt":"Reinforcement Learning (RL) has been pivotal in recent robotics milestones and is poised to play a prominent role in the future. However, these advances can rely on proprietary simulators, expensive hardware, and a daunting range of tools and skills. As a result, broader communities are disconnecting from the state-of-the-art; education curricula are poorly equipped to teach indispensable modern robotics skills involving hardware, deployment, and iterative development. To address this gap between the broader and scientific communities, we contribute Wheeled Lab, an ecosystem which integrates a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.07380","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/2502.07380/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":"2502.07380","created_at":"2026-07-05T12:01:57.439478+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.07380v2","created_at":"2026-07-05T12:01:57.439478+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.07380","created_at":"2026-07-05T12:01:57.439478+00:00"},{"alias_kind":"pith_short_12","alias_value":"CPBS3KETDPTY","created_at":"2026-07-05T12:01:57.439478+00:00"},{"alias_kind":"pith_short_16","alias_value":"CPBS3KETDPTYFAK4","created_at":"2026-07-05T12:01:57.439478+00:00"},{"alias_kind":"pith_short_8","alias_value":"CPBS3KET","created_at":"2026-07-05T12:01:57.439478+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/CPBS3KETDPTYFAK4QE3I6CQKYN","json":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN.json","graph_json":"https://pith.science/api/pith-number/CPBS3KETDPTYFAK4QE3I6CQKYN/graph.json","events_json":"https://pith.science/api/pith-number/CPBS3KETDPTYFAK4QE3I6CQKYN/events.json","paper":"https://pith.science/paper/CPBS3KET"},"agent_actions":{"view_html":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN","download_json":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN.json","view_paper":"https://pith.science/paper/CPBS3KET","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.07380&json=true","fetch_graph":"https://pith.science/api/pith-number/CPBS3KETDPTYFAK4QE3I6CQKYN/graph.json","fetch_events":"https://pith.science/api/pith-number/CPBS3KETDPTYFAK4QE3I6CQKYN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN/action/storage_attestation","attest_author":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN/action/author_attestation","sign_citation":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN/action/citation_signature","submit_replication":"https://pith.science/pith/CPBS3KETDPTYFAK4QE3I6CQKYN/action/replication_record"}},"created_at":"2026-07-05T12:01:57.439478+00:00","updated_at":"2026-07-05T12:01:57.439478+00:00"}