Multimodal Progress-Residual Fusion for Anticipating Navigation Retreat in Robotic Flexible Endoscopy
Multimodal Progress-Residual Fusion for Anticipating Navigation Retreat in Robotic Flexible Endoscopy
This research presents Multimodal Progress-Residual Fusion (MPRF), a causal model designed to anticipate operator retreat decisions during robotic flexible endoscopy. By fusing electromagnetic tracking, endoscopic video, and motor intent data against a nominal-progress baseline, the system predicts navigational mismatches caused by friction or deformation. Evaluated on a 150-episode colon-phantom dataset, MPRF achieves an AUPRC of 0.580 +/- 0.007, outperforming reduced-modality controls (0.511). The work establishes a foundation for behavioral assistance systems in operator-controlled navigation.
The study introduces Multimodal Progress-Residual Fusion (MPRF), a causal model tested on a 150-episode colon-phantom collection, which achieves an AUPRC of 0.580 +/- 0.007 for anticipating operator retreat during flexible endoscopy navigation.
Source: arXiv Robotics — research abstracts · Read original article ↗
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isual scene. We introduce Multimodal Progress-Residual Fusion (MPRF), a causal model that anticipates operator retreat from commands, electromagnetic (EM) tracking, and endoscopic video. A nominal-progress model predicts the response expected in normal or successful navigation; a temporal predictor combines its EM residual with all three observed modalities. In a 150-episode colon-phantom collection, MPRF achieves 0.
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arXiv:2610.31028v3 Announce Type: replace Abstract: Flexible robotic endoscopes provide access through tortuous anatomy, where friction, deformation, and wall interaction separate commanded insertion from useful distal progress. Operators interpret this mismatch and retreat to recover a navigable configuration. Recognizing the approach to that decision requires relating motor intent to distal response and the local v
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580 +/- 0.007 AUPRC across three seeds, compared with 0.511 for the strongest reduced-modality control. Complete multimodal histories provide the principal ranking advantage, while the residual adds an explicit intent-response representation with a small, uncertain increment over raw fusion. Analysis of frozen alarms relates warning timing to the behavioral label and explains the increase in event recall under a long
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er matching window. These results establish a basis for behavioral assistance during operator-controlled navigation.
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Multimodal Progress-Residual Fusion for Anticipating Navigation Retreat in Robotic Flexible Endoscopy
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Source：arXiv Robotics — research abstracts · arxiv.org