{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XZVPKX2R7AF4NER43RPBIEIZ47","short_pith_number":"pith:XZVPKX2R","schema_version":"1.0","canonical_sha256":"be6af55f51f80bc6923cdc5e141119e7e3f14b07eeef863d306cfe7e957a44b9","source":{"kind":"arxiv","id":"2607.16630","version":1},"attestation_state":"computed","paper":{"title":"AI-Augmented Model Predictive Control for Safe and Adaptive Rendezvous and Proximity Operations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cagri Kilic, Di Wu, Luca Sportelli, Tyler Barr","submitted_at":"2026-07-18T04:20:23Z","abstract_excerpt":"Autonomous rendezvous and proximity operations (RPO) in adversarial orbital environments require guidance architectures balancing target pursuit, safety preservation, and real-time adaptability under dynamically evolving interaction conditions. Although learning-based approaches show promise, their application to safety-critical orbital robotics remains limited by concerns regarding interpretability, robustness, and constraint awareness. This work presents an adaptive Model Predictive Control (MPC) framework for autonomous spacecraft RPO in multi-agent adversarial scenarios. The proposed archi"},"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":"2607.16630","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-18T04:20:23Z","cross_cats_sorted":[],"title_canon_sha256":"cc3d3816a71172740c0f6067ffae18e8ce94b3fb4355df59e91ab40ea9577d1b","abstract_canon_sha256":"bb0d1339c02e43bef2b109381176098b8cd1f081e7e9adb20b1abdbe0becb8c1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T01:20:19.203956Z","signature_b64":"xVxtJJoIEQ4DeJHYb0uKegzoXa5rHYZJZjZRFLtrT1BDBgm8VT6z1M9HyNxrM19z8B/swUC2CGuEfbggoQi+DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"be6af55f51f80bc6923cdc5e141119e7e3f14b07eeef863d306cfe7e957a44b9","last_reissued_at":"2026-07-21T01:20:19.201644Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T01:20:19.201644Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AI-Augmented Model Predictive Control for Safe and Adaptive Rendezvous and Proximity Operations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cagri Kilic, Di Wu, Luca Sportelli, Tyler Barr","submitted_at":"2026-07-18T04:20:23Z","abstract_excerpt":"Autonomous rendezvous and proximity operations (RPO) in adversarial orbital environments require guidance architectures balancing target pursuit, safety preservation, and real-time adaptability under dynamically evolving interaction conditions. Although learning-based approaches show promise, their application to safety-critical orbital robotics remains limited by concerns regarding interpretability, robustness, and constraint awareness. This work presents an adaptive Model Predictive Control (MPC) framework for autonomous spacecraft RPO in multi-agent adversarial scenarios. The proposed archi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16630","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/2607.16630/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":"2607.16630","created_at":"2026-07-21T01:20:19.202160+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.16630v1","created_at":"2026-07-21T01:20:19.202160+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16630","created_at":"2026-07-21T01:20:19.202160+00:00"},{"alias_kind":"pith_short_12","alias_value":"XZVPKX2R7AF4","created_at":"2026-07-21T01:20:19.202160+00:00"},{"alias_kind":"pith_short_16","alias_value":"XZVPKX2R7AF4NER4","created_at":"2026-07-21T01:20:19.202160+00:00"},{"alias_kind":"pith_short_8","alias_value":"XZVPKX2R","created_at":"2026-07-21T01:20:19.202160+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/XZVPKX2R7AF4NER43RPBIEIZ47","json":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47.json","graph_json":"https://pith.science/api/pith-number/XZVPKX2R7AF4NER43RPBIEIZ47/graph.json","events_json":"https://pith.science/api/pith-number/XZVPKX2R7AF4NER43RPBIEIZ47/events.json","paper":"https://pith.science/paper/XZVPKX2R"},"agent_actions":{"view_html":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47","download_json":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47.json","view_paper":"https://pith.science/paper/XZVPKX2R","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.16630&json=true","fetch_graph":"https://pith.science/api/pith-number/XZVPKX2R7AF4NER43RPBIEIZ47/graph.json","fetch_events":"https://pith.science/api/pith-number/XZVPKX2R7AF4NER43RPBIEIZ47/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47/action/storage_attestation","attest_author":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47/action/author_attestation","sign_citation":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47/action/citation_signature","submit_replication":"https://pith.science/pith/XZVPKX2R7AF4NER43RPBIEIZ47/action/replication_record"}},"created_at":"2026-07-21T01:20:19.202160+00:00","updated_at":"2026-07-21T01:20:19.202160+00:00"}