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Markerless 6D Pose Estimation Framework Enhances Surgical Manipulator Control

Researchers have developed MarUco, a novel markerless framework for estimating the 6D pose of surgical continuum manipulators using stereo vision. This system aims to improve closed-loop control accuracy by compensating for the nonlinear hysteresis inherent in these flexible instruments. MarUco integrates multiple visual features and employs a self-supervised adaptation method to minimize sim-to-real errors, achieving a mean terminal translation error of 1.8 mm in experiments, which represents an 88% reduction compared to uncompensated control. AI

IMPACT This framework could enable more precise robotic surgery by improving real-time pose estimation for flexible instruments.

RANK_REASON The cluster contains a research paper detailing a new framework for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Markerless 6D Pose Estimation Framework Enhances Surgical Manipulator Control

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The cluster contains a research paper detailing a new framework for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Junhyun Park, Chunggil An, Myeongbo Park, Ihsan Ullah, Sihyeong Park, Minho Hwang ·

    MarUco: A Markerless 6D Pose Estimation Framework for Closed-Loop Control of Surgical Continuum Manipulators

    arXiv:2602.16365v2 Announce Type: replace-cross Abstract: Flexible endoscopic continuum manipulators offer high dexterity and access to complex anatomy, but nonlinear hysteresis limits feedforward control accuracy. Closed-loop control can compensate for these errors but requires …