{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:AW7NMDTZMZOZKS7MKAUBHUWNF6","short_pith_number":"pith:AW7NMDTZ","schema_version":"1.0","canonical_sha256":"05bed60e79665d954bec502813d2cd2fa9d415f5eb00dca3b00ab8e6b0f1234e","source":{"kind":"arxiv","id":"1811.05929","version":1},"attestation_state":"computed","paper":{"title":"A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Anca D. Dragan, Andrea Bajcsy, Claire J. Tomlin, David Fridovich-Keil, Jaime F. Fisac, Sampada Deglurkar, Sylvia L. Herbert","submitted_at":"2018-11-14T17:56:54Z","abstract_excerpt":"Robust motion planning is a well-studied problem in the robotics literature, yet current algorithms struggle to operate scalably and safely in the presence of other moving agents, such as humans. This paper introduces a novel framework for robot navigation that accounts for high-order system dynamics and maintains safety in the presence of external disturbances, other robots, and non-deterministic intentional agents. Our approach precomputes a tracking error margin for each robot, generates confidence-aware human motion predictions, and coordinates multiple robots with a sequential priority or"},"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":"1811.05929","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-11-14T17:56:54Z","cross_cats_sorted":[],"title_canon_sha256":"55d4500b7d8d8c3de895bc6d88fee8d15839f41c53b39bed0a08052dae8fcb7a","abstract_canon_sha256":"0865c8ea53a8d8155be0220ec2daa9c821be328d3579f84f4d1c49fdf53924e7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:41.819585Z","signature_b64":"p7Yp2RRqIoaVpnGakmEM7EDURhZl2GHUhsTGEU6dKhLcblidGYezA3cwXZOEweEry8gjsmr2emqon52BQ8/JBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05bed60e79665d954bec502813d2cd2fa9d415f5eb00dca3b00ab8e6b0f1234e","last_reissued_at":"2026-05-18T00:00:41.819156Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:41.819156Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Anca D. Dragan, Andrea Bajcsy, Claire J. Tomlin, David Fridovich-Keil, Jaime F. Fisac, Sampada Deglurkar, Sylvia L. Herbert","submitted_at":"2018-11-14T17:56:54Z","abstract_excerpt":"Robust motion planning is a well-studied problem in the robotics literature, yet current algorithms struggle to operate scalably and safely in the presence of other moving agents, such as humans. This paper introduces a novel framework for robot navigation that accounts for high-order system dynamics and maintains safety in the presence of external disturbances, other robots, and non-deterministic intentional agents. Our approach precomputes a tracking error margin for each robot, generates confidence-aware human motion predictions, and coordinates multiple robots with a sequential priority or"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.05929","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":""},"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":"1811.05929","created_at":"2026-05-18T00:00:41.819222+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.05929v1","created_at":"2026-05-18T00:00:41.819222+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.05929","created_at":"2026-05-18T00:00:41.819222+00:00"},{"alias_kind":"pith_short_12","alias_value":"AW7NMDTZMZOZ","created_at":"2026-05-18T12:32:13.499390+00:00"},{"alias_kind":"pith_short_16","alias_value":"AW7NMDTZMZOZKS7M","created_at":"2026-05-18T12:32:13.499390+00:00"},{"alias_kind":"pith_short_8","alias_value":"AW7NMDTZ","created_at":"2026-05-18T12:32:13.499390+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/AW7NMDTZMZOZKS7MKAUBHUWNF6","json":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6.json","graph_json":"https://pith.science/api/pith-number/AW7NMDTZMZOZKS7MKAUBHUWNF6/graph.json","events_json":"https://pith.science/api/pith-number/AW7NMDTZMZOZKS7MKAUBHUWNF6/events.json","paper":"https://pith.science/paper/AW7NMDTZ"},"agent_actions":{"view_html":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6","download_json":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6.json","view_paper":"https://pith.science/paper/AW7NMDTZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.05929&json=true","fetch_graph":"https://pith.science/api/pith-number/AW7NMDTZMZOZKS7MKAUBHUWNF6/graph.json","fetch_events":"https://pith.science/api/pith-number/AW7NMDTZMZOZKS7MKAUBHUWNF6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6/action/storage_attestation","attest_author":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6/action/author_attestation","sign_citation":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6/action/citation_signature","submit_replication":"https://pith.science/pith/AW7NMDTZMZOZKS7MKAUBHUWNF6/action/replication_record"}},"created_at":"2026-05-18T00:00:41.819222+00:00","updated_at":"2026-05-18T00:00:41.819222+00:00"}