Publications
Each entry states where the work actually is: an archived dataset, a manuscript in preparation, a preprint, under review, accepted, or peer-reviewed and published. Nothing is listed above its true status, and no draft is described as a paper.
Datasets
Dataset — archived and citable2026
Early Failure Prediction and Recovery for Mobile Robot Navigation: Core Evidence
Emmanuel Alabi Olasubomi
Zenodo
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Core evidence for a preregistered ROS 2/Gazebo/Nav2 study of early navigation-failure prediction and guarded recovery: every report and manifest, the frozen configurations, and all trained checkpoints with their normalisation and training records. Both confirmatory hypotheses were not supported.
Dataset — archived and citable2026
Risk-Calibrated Semantic Navigation Under Distribution Shift: confirmatory evaluation dataset
Emmanuel Alabi Olasubomi
Zenodo
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The confirmatory core dataset for the risk-calibrated semantic navigation study: 6,840 episode summaries across four navigation systems under controlled distribution shift, with the manifest, exclusion ledger and release inventory needed to reproduce every reported result. Archived separately from the approximately 1 TB retained bag corpus.
Manuscripts in preparation
Manuscript in preparation2026
Better Calibration Without Demonstrated Safety Gains: Risk-Calibrated Semantic Navigation Under Distribution Shift
Emmanuel Alabi Olasubomi
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A preregistered ROS 2 and Gazebo benchmark testing whether calibrated semantic perception uncertainty, converted into navigation cost, improves closed-loop outcomes under controlled distribution shift. Calibration improved and clean-route efficiency held; the preregistered collision-reduction and severity-interaction hypotheses did not pass.
Manuscript in preparation2026
Early Warning Without Demonstrated Recovery Benefit: Failure Prediction and Guarded Recovery for Mobile Robot Navigation
Emmanuel Alabi Olasubomi
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A preregistered ROS 2/Gazebo/Nav2 study of whether mission-ending navigation failure can be forecast early enough to support a bounded recovery, and whether acting on the forecast improves the mission. Warning was timely where it occurred, with a median useful lead time of 3.8 s, but the primary recall interval included zero and guarded recovery did not improve completion. Both confirmatory hypotheses are unsupported, leaving a signal-to-decision gap.
Manuscript in preparation2026
Reproducing a Classic Driver Drowsiness Pipeline: Where the Errors Actually Come From
Emmanuel Alabi
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A leakage-safe reproduction of a widely replicated eye-state and temporal-alerting pipeline under a subject-independent protocol. An oracle-classifier decomposition locates the residual false alerts in the temporal decision rule rather than in classification error, above a threshold of classifier competence.