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Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation — arXiv:2610.09302

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.09302
License (as archived): CC0-1.0
Archived: 2026-10-08T12:48:59.379Z
SHA-256 of the archived text: e24fe7180dfd42116152419a6ea530642132e111df5d853e6112262b6dfe195a
Stable URL of this page: https://metraipolis.com/documento/dc_dbb409cf83f4

How to cite

Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation — arXiv:2610.09302 — arXiv (en), https://arxiv.org/abs/2610.09302 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_dbb409cf83f4 (Metraipolis archive dc_dbb409cf83f4, sha256 e24fe7180dfd42116152419a6ea530642132e111df5d853e6112262b6dfe195a)

BibTeX

@misc{dcdbb409cf83f4,
  title = {Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation — arXiv:2610.09302},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.09302},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_dbb409cf83f4; sha256 e24fe7180dfd42116152419a6ea530642132e111df5d853e6112262b6dfe195a},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.09302. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Safe navigation in dynamic environments requires robots to plan under obstacle predictions whose errors are uncertain, non-stationary, and can induce rare but safety-critical failures. Existing control-barrier-function safety filters can reject immediately unsafe controls, but they provide little guidance on when the current finite-horizon planning mode itself is becoming unsafe as prediction uncertainty evolves. We propose Conformal Event-Triggered Risk-Certified Replanning (\emph{CERT-Replan}), a framework that uses calibrated barrier risk as an early-warning signal for replanning. CERT-Replan calibrates horizon-indexed obstacle-prediction residuals online and uses the resulting uncertainty radii to evaluate dynamic-obstacle safety margins. A one-step safety filter protects the next applied control, while a horizon-level risk monitor evaluates the upper-tail CVaR of predicted barrier-violation losses along the current MPC rollout. When this risk exceeds an allocated budget, CERT-Replan rejects the current planning mode and selects a lower-risk alternative, such as a different speed profile, corridor, or homotopy class, rather than repeatedly correcting the same nominal plan. In a non-stationary benchmark, CERT-Replan achieves an \(83.3\%\) collision reduction relative to the safety-filter-only baseline \textcolor{black}{and a \(77.8\%\) reduction relative to simple replanning triggers}, while reducing average safety-filter intervention by \(32.4\%\). \textcolor{black}{With Trajectron++, CERT-Replan achieves \(96\%\) collision-free operation. Hardware experiments and onboard runtime profiling demonstrate computational feasibility.}

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.RO, nuovi lavori del giorno).
Categorie arXiv: Robotics (cs.RO) ; Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2610.09302 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T12:18:30.516Z dalla pagina https://arxiv.org/list/cs.RO/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).