{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:VX7UX3KO3SJ3WAXFWIQVZFICE3","short_pith_number":"pith:VX7UX3KO","schema_version":"1.0","canonical_sha256":"adff4bed4edc93bb02e5b2215c950226e5600c8386ee9c2962d54335c5001720","source":{"kind":"arxiv","id":"2410.00572","version":2},"attestation_state":"computed","paper":{"title":"Obstacle-Avoidant Leader Following with a Quadruped Robot","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Andrei Cramariuc, Carmen Scheidemann, Jia-Ruei Chiu, Joris Chomarat, Lennart Werner, Marco Hutter, Roland Siegwart, Victor Reijgwart","submitted_at":"2024-10-01T10:40:18Z","abstract_excerpt":"Personal mobile robotic assistants are expected to find wide applications in industry and healthcare. For example, people with limited mobility can benefit from robots helping with daily tasks, or construction workers can have robots perform precision monitoring tasks on-site. However, manually steering a robot while in motion requires significant concentration from the operator, especially in tight or crowded spaces. This reduces walking speed, and the constant need for vigilance increases fatigue and, thus, the risk of accidents. This work presents a virtual leash with which a robot can natu"},"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":"2410.00572","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-10-01T10:40:18Z","cross_cats_sorted":[],"title_canon_sha256":"614297e4474ed39a702183d73f596906151e910c803a9b469a253e4eb1a10287","abstract_canon_sha256":"8b2966de40a64f0db71b85c158148128780a2bcf86d3decd392ff42e844ec7c4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:26:08.084709Z","signature_b64":"D0H/mj3yXyGFi4k7WWT3OJ8RPn0KwuujF+pDJii4UfwTRKlL9kEMBWwHpBjw+b7kYR3S9CR6f0w8+uAoGEwIAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"adff4bed4edc93bb02e5b2215c950226e5600c8386ee9c2962d54335c5001720","last_reissued_at":"2026-07-05T10:26:08.084198Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:26:08.084198Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Obstacle-Avoidant Leader Following with a Quadruped Robot","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Andrei Cramariuc, Carmen Scheidemann, Jia-Ruei Chiu, Joris Chomarat, Lennart Werner, Marco Hutter, Roland Siegwart, Victor Reijgwart","submitted_at":"2024-10-01T10:40:18Z","abstract_excerpt":"Personal mobile robotic assistants are expected to find wide applications in industry and healthcare. For example, people with limited mobility can benefit from robots helping with daily tasks, or construction workers can have robots perform precision monitoring tasks on-site. However, manually steering a robot while in motion requires significant concentration from the operator, especially in tight or crowded spaces. This reduces walking speed, and the constant need for vigilance increases fatigue and, thus, the risk of accidents. This work presents a virtual leash with which a robot can natu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.00572","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/2410.00572/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":"2410.00572","created_at":"2026-07-05T10:26:08.084264+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.00572v2","created_at":"2026-07-05T10:26:08.084264+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.00572","created_at":"2026-07-05T10:26:08.084264+00:00"},{"alias_kind":"pith_short_12","alias_value":"VX7UX3KO3SJ3","created_at":"2026-07-05T10:26:08.084264+00:00"},{"alias_kind":"pith_short_16","alias_value":"VX7UX3KO3SJ3WAXF","created_at":"2026-07-05T10:26:08.084264+00:00"},{"alias_kind":"pith_short_8","alias_value":"VX7UX3KO","created_at":"2026-07-05T10:26:08.084264+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2509.10796","citing_title":"Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following","ref_index":39,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3","json":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3.json","graph_json":"https://pith.science/api/pith-number/VX7UX3KO3SJ3WAXFWIQVZFICE3/graph.json","events_json":"https://pith.science/api/pith-number/VX7UX3KO3SJ3WAXFWIQVZFICE3/events.json","paper":"https://pith.science/paper/VX7UX3KO"},"agent_actions":{"view_html":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3","download_json":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3.json","view_paper":"https://pith.science/paper/VX7UX3KO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.00572&json=true","fetch_graph":"https://pith.science/api/pith-number/VX7UX3KO3SJ3WAXFWIQVZFICE3/graph.json","fetch_events":"https://pith.science/api/pith-number/VX7UX3KO3SJ3WAXFWIQVZFICE3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3/action/storage_attestation","attest_author":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3/action/author_attestation","sign_citation":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3/action/citation_signature","submit_replication":"https://pith.science/pith/VX7UX3KO3SJ3WAXFWIQVZFICE3/action/replication_record"}},"created_at":"2026-07-05T10:26:08.084264+00:00","updated_at":"2026-07-05T10:26:08.084264+00:00"}