{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:IBUCSIVPZZIDF7AIPFTGMIGFWT","short_pith_number":"pith:IBUCSIVP","canonical_record":{"source":{"id":"2211.01576","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-11-03T04:12:04Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"dafe9da5fadfcc6c3b311a807d8997c665eefd1f9a60f11ddaaf334eeb611fd5","abstract_canon_sha256":"4bf46d01e4666088f5c640d077a7869e7965a72df851f702d903384e32eb7b5f"},"schema_version":"1.0"},"canonical_sha256":"40682922afce5032fc0879666620c5b4f2ce075ec9b9b48d9c508a53714922b5","source":{"kind":"arxiv","id":"2211.01576","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.01576","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"arxiv_version","alias_value":"2211.01576v2","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.01576","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_12","alias_value":"IBUCSIVPZZID","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_16","alias_value":"IBUCSIVPZZIDF7AI","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_8","alias_value":"IBUCSIVP","created_at":"2026-07-05T06:12:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:IBUCSIVPZZIDF7AIPFTGMIGFWT","target":"record","payload":{"canonical_record":{"source":{"id":"2211.01576","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-11-03T04:12:04Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"dafe9da5fadfcc6c3b311a807d8997c665eefd1f9a60f11ddaaf334eeb611fd5","abstract_canon_sha256":"4bf46d01e4666088f5c640d077a7869e7965a72df851f702d903384e32eb7b5f"},"schema_version":"1.0"},"canonical_sha256":"40682922afce5032fc0879666620c5b4f2ce075ec9b9b48d9c508a53714922b5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:12:23.093757Z","signature_b64":"FINDcepQIlwxZbs/0uX7LA1aSCPuA9dtXcJALGLBDB8LypWaYh5tW0Q86foQbwZXxrfIXX9EJ9Y6cUGQHpCnCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40682922afce5032fc0879666620c5b4f2ce075ec9b9b48d9c508a53714922b5","last_reissued_at":"2026-07-05T06:12:23.093272Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:12:23.093272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.01576","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:12:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ludUj2v7ZKKFw5v2ZHw6Jq2L/vS4aw6HERpk48jsHuncwsyOSKilGa27DdeTesUR2j8MMNl6LWq49HmOnBi0Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T10:57:57.932761Z"},"content_sha256":"8bb41262e0ca74e25baa1b2eef2c6286ddc68adda36255050029a6fa7fa799bf","schema_version":"1.0","event_id":"sha256:8bb41262e0ca74e25baa1b2eef2c6286ddc68adda36255050029a6fa7fa799bf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:IBUCSIVPZZIDF7AIPFTGMIGFWT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Caelan Reed Garrett, Dieter Fox, Leslie Kaelbling, Tom\\'as Lozano-P\\'erez, Zhutian Yang","submitted_at":"2022-11-03T04:12:04Z","abstract_excerpt":"We present a learning-enabled Task and Motion Planning (TAMP) algorithm for solving mobile manipulation problems in environments with many articulated and movable obstacles. Our idea is to bias the search procedure of a traditional TAMP planner with a learned plan feasibility predictor. The core of our algorithm is PIGINet, a novel Transformer-based learning method that takes in a task plan, the goal, and the initial state, and predicts the probability of finding motion trajectories associated with the task plan. We integrate PIGINet within a TAMP planner that generates a diverse set of high-l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.01576","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/2211.01576/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:12:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0IvYENK3u5t5eDVw+FJpurRkXJ9zz1YHuD/c0zKO1udf9y3sl8wDhCxuN7Q+OkRPbs2zwI0He9AJbr7LI9UUBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T10:57:57.933306Z"},"content_sha256":"d737f80b5439d4da54f9496b52309231d98e42e322124522184a45c66156763b","schema_version":"1.0","event_id":"sha256:d737f80b5439d4da54f9496b52309231d98e42e322124522184a45c66156763b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT/bundle.json","state_url":"https://pith.science/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-15T10:57:57Z","links":{"resolver":"https://pith.science/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT","bundle":"https://pith.science/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT/bundle.json","state":"https://pith.science/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IBUCSIVPZZIDF7AIPFTGMIGFWT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:IBUCSIVPZZIDF7AIPFTGMIGFWT","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"4bf46d01e4666088f5c640d077a7869e7965a72df851f702d903384e32eb7b5f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-11-03T04:12:04Z","title_canon_sha256":"dafe9da5fadfcc6c3b311a807d8997c665eefd1f9a60f11ddaaf334eeb611fd5"},"schema_version":"1.0","source":{"id":"2211.01576","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.01576","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"arxiv_version","alias_value":"2211.01576v2","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.01576","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_12","alias_value":"IBUCSIVPZZID","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_16","alias_value":"IBUCSIVPZZIDF7AI","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_8","alias_value":"IBUCSIVP","created_at":"2026-07-05T06:12:23Z"}],"graph_snapshots":[{"event_id":"sha256:d737f80b5439d4da54f9496b52309231d98e42e322124522184a45c66156763b","target":"graph","created_at":"2026-07-05T06:12:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2211.01576/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a learning-enabled Task and Motion Planning (TAMP) algorithm for solving mobile manipulation problems in environments with many articulated and movable obstacles. Our idea is to bias the search procedure of a traditional TAMP planner with a learned plan feasibility predictor. The core of our algorithm is PIGINet, a novel Transformer-based learning method that takes in a task plan, the goal, and the initial state, and predicts the probability of finding motion trajectories associated with the task plan. We integrate PIGINet within a TAMP planner that generates a diverse set of high-l","authors_text":"Caelan Reed Garrett, Dieter Fox, Leslie Kaelbling, Tom\\'as Lozano-P\\'erez, Zhutian Yang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-11-03T04:12:04Z","title":"Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.01576","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8bb41262e0ca74e25baa1b2eef2c6286ddc68adda36255050029a6fa7fa799bf","target":"record","created_at":"2026-07-05T06:12:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"4bf46d01e4666088f5c640d077a7869e7965a72df851f702d903384e32eb7b5f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-11-03T04:12:04Z","title_canon_sha256":"dafe9da5fadfcc6c3b311a807d8997c665eefd1f9a60f11ddaaf334eeb611fd5"},"schema_version":"1.0","source":{"id":"2211.01576","kind":"arxiv","version":2}},"canonical_sha256":"40682922afce5032fc0879666620c5b4f2ce075ec9b9b48d9c508a53714922b5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40682922afce5032fc0879666620c5b4f2ce075ec9b9b48d9c508a53714922b5","first_computed_at":"2026-07-05T06:12:23.093272Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:12:23.093272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FINDcepQIlwxZbs/0uX7LA1aSCPuA9dtXcJALGLBDB8LypWaYh5tW0Q86foQbwZXxrfIXX9EJ9Y6cUGQHpCnCA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:12:23.093757Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.01576","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8bb41262e0ca74e25baa1b2eef2c6286ddc68adda36255050029a6fa7fa799bf","sha256:d737f80b5439d4da54f9496b52309231d98e42e322124522184a45c66156763b"],"state_sha256":"ecd1cc876464b8be99939bd6f68a9d5aab5aa95abb531aaffb18986e068ee1dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ccLwoWmaSyiPEIXKrU9w3Oc2zzBH8jstFBQdQaHpgsPspbdZ7jksvtU0k3M4N+2YMUqMpraHqdNrrH3hImZaBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T10:57:57.936967Z","bundle_sha256":"80648a1e44e37364fbd58b92fc1ed43f84000ff76884a9083c041d4974672a0e"}}