AquaMend: Minimal Re-probing and Conditional Rollback for Latent-Belief Failures in Embodied Agents

Abstract:Physical changes or sensing errors can invalidate embodied agents' task-relevant beliefs. AquaMend compares re-probing, rollback, and supported continuation on a probe-belief-action graph under an expected-loss objective covering sensing, physical recovery, and uncorrected failures. A joint posterior guides a one-step policy with conditional detection-power screening. The per-belief three-way optimum requires independence, separability, and fully resolving probes; the general policy has no global optimality guarantee. Across 32 paired scenarios in a self-constructed simulation benchmark, AquaMend recovers in 28/32 cases and reduces mean complete loss by 21.6% versus restart. Its paired loss difference from decision-theoretic troubleshooting (DTT) is not statistically significant after Holm correction. Against the all-candidate ablation, online decision time decreases by 12.3% overall but increases by 3.4% in the uncovered late stage.

29 pages, 1 figure. Yufan Liu, Shang Luo, and Yang Liu contributed equally. Corresponding author: Bin Chong

Robotics (cs.RO)

arXiv:2609.28973 [cs.RO]

(or arXiv:2609.28973v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.28973 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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