{"paper":{"title":"Ultrafast Sampling-based Kinodynamic Planning via Differential Flatness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"FLASK solves kinodynamic planning for flat robots by turning boundary problems into analytical flat-output trajectories.","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Clayton W. Ramsey, Lydia E. Kavraki, Thai Duong, Wil Thomason, Zachary Kingston","submitted_at":"2026-03-17T01:53:10Z","abstract_excerpt":"Motion planning under dynamics constraints, i.e, kinodynamic planning, enables safe robot operation by generating dynamically feasible trajectories that the robot can accurately track. For high-DOF robots such as manipulators, sampling-based motion planners are commonly used, especially for complex tasks in cluttered environments. However, enforcing constraints on robot dynamics in such planners requires solving either challenging two-point boundary value problems (BVPs) or propagating robot dynamics, both of which cause computational bottlenecks that drastically increase planning times. Meanw"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Our framework is fast, exact, and compatible with any sampling-based motion planner, while offering theoretical guarantees on probabilistic exhaustibility and asymptotic optimality based on the closed-form BVP solutions.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The target robot systems must be differentially flat so that an analytical time-parameterized solution of the two-point boundary-value problem exists in the flat output space.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"FLASK uses differential flatness for closed-form BVP solutions in sampling-based kinodynamic planning, delivering microsecond-scale times with theoretical guarantees for flat systems like manipulators and vehicles.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"FLASK solves kinodynamic planning for flat robots by turning boundary problems into analytical flat-output trajectories.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"9bb4f6aef09cede5e604ee39e09bb5d4b35948046daba7c602080f4f9d715bcf"},"source":{"id":"2603.16059","kind":"arxiv","version":3},"verdict":{"id":"f00fcaf6-9e21-42df-b763-aa04afeb128b","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T10:45:11.296621Z","strongest_claim":"Our framework is fast, exact, and compatible with any sampling-based motion planner, while offering theoretical guarantees on probabilistic exhaustibility and asymptotic optimality based on the closed-form BVP solutions.","one_line_summary":"FLASK uses differential flatness for closed-form BVP solutions in sampling-based kinodynamic planning, delivering microsecond-scale times with theoretical guarantees for flat systems like manipulators and vehicles.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The target robot systems must be differentially flat so that an analytical time-parameterized solution of the two-point boundary-value problem exists in the flat output space.","pith_extraction_headline":"FLASK solves kinodynamic planning for flat robots by turning boundary problems into analytical flat-output trajectories."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2603.16059/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"}