{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:WM5SSRQFGEURS6T5SCW7HCCPUJ","short_pith_number":"pith:WM5SSRQF","schema_version":"1.0","canonical_sha256":"b33b2946053129197a7d90adf3884fa24feae7a29d75cf1c89d1768c6b8509ac","source":{"kind":"arxiv","id":"2202.12385","version":1},"attestation_state":"computed","paper":{"title":"A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Farbod Farshidian, Jean-Pierre Sleiman, Jia-Ruei Chiu, Marco Hutter, Mayank Mittal","submitted_at":"2022-02-24T22:11:08Z","abstract_excerpt":"In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft constraints within a Model Predictive Control (MPC) scheme that solves a multi-contact optimal control problem. By penalizing the signed distances among a set of representative primitive collision bodies, the robot is able to safely execute a variety of dynamic maneuvers while preventing any self-collisions. Moreover, collision-free navigation and manipulation in both static and dynamic environments are made viable th"},"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":"2202.12385","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-02-24T22:11:08Z","cross_cats_sorted":[],"title_canon_sha256":"40168963d7b388c40c46c3ec8e0024a2e975e43f914a221898b69a2ab5e4f7f0","abstract_canon_sha256":"f1188668605202b798db23d8db26a30cbdfe132bf42547ea925ad8f025e98421"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:59:54.710899Z","signature_b64":"/JUbBxoJx05kvXprEMt5Z7ZqiP8cB1RUNS0xWpMZ5x5Ig56IMzeyQnnxwS7hi2EznRaCV6cErJYsGbwS95TFCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b33b2946053129197a7d90adf3884fa24feae7a29d75cf1c89d1768c6b8509ac","last_reissued_at":"2026-07-05T03:59:54.710517Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:59:54.710517Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Farbod Farshidian, Jean-Pierre Sleiman, Jia-Ruei Chiu, Marco Hutter, Mayank Mittal","submitted_at":"2022-02-24T22:11:08Z","abstract_excerpt":"In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft constraints within a Model Predictive Control (MPC) scheme that solves a multi-contact optimal control problem. By penalizing the signed distances among a set of representative primitive collision bodies, the robot is able to safely execute a variety of dynamic maneuvers while preventing any self-collisions. Moreover, collision-free navigation and manipulation in both static and dynamic environments are made viable th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.12385","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2202.12385/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":"2202.12385","created_at":"2026-07-05T03:59:54.710573+00:00"},{"alias_kind":"arxiv_version","alias_value":"2202.12385v1","created_at":"2026-07-05T03:59:54.710573+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.12385","created_at":"2026-07-05T03:59:54.710573+00:00"},{"alias_kind":"pith_short_12","alias_value":"WM5SSRQFGEUR","created_at":"2026-07-05T03:59:54.710573+00:00"},{"alias_kind":"pith_short_16","alias_value":"WM5SSRQFGEURS6T5","created_at":"2026-07-05T03:59:54.710573+00:00"},{"alias_kind":"pith_short_8","alias_value":"WM5SSRQF","created_at":"2026-07-05T03:59:54.710573+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.04276","citing_title":"Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics","ref_index":7,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ","json":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ.json","graph_json":"https://pith.science/api/pith-number/WM5SSRQFGEURS6T5SCW7HCCPUJ/graph.json","events_json":"https://pith.science/api/pith-number/WM5SSRQFGEURS6T5SCW7HCCPUJ/events.json","paper":"https://pith.science/paper/WM5SSRQF"},"agent_actions":{"view_html":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ","download_json":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ.json","view_paper":"https://pith.science/paper/WM5SSRQF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2202.12385&json=true","fetch_graph":"https://pith.science/api/pith-number/WM5SSRQFGEURS6T5SCW7HCCPUJ/graph.json","fetch_events":"https://pith.science/api/pith-number/WM5SSRQFGEURS6T5SCW7HCCPUJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ/action/storage_attestation","attest_author":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ/action/author_attestation","sign_citation":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ/action/citation_signature","submit_replication":"https://pith.science/pith/WM5SSRQFGEURS6T5SCW7HCCPUJ/action/replication_record"}},"created_at":"2026-07-05T03:59:54.710573+00:00","updated_at":"2026-07-05T03:59:54.710573+00:00"}