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September 8, 2026International Journal of Medical Robotics and Computer Assisted Surgery

Adaptive Grid Search Method Using Dynamic Step‐Size Adjustment for Robot‐Tissue Interaction Force Estimation

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Authors

YZYinzhi ZhuHLHongbing Li

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Overview

Experimental study demonstrates improved force estimation accuracy in surgical robotics via dynamic step-size optimization, suggesting safer minimally invasive procedures without physical sensors.

Key Points

  • To develop an adaptive grid search algorithm with dynamic step-size adjustment that accurately estimates robot-tissue interaction forces in minimally invasive surgery without requiring physical sensors.
  • Designed an adaptive grid search framework to optimize Hunt-Crossley contact model parameters for robotic force estimation.
  • Implemented dynamic step-size adjustment governed by real-time estimation error to balance broad parameter exploration and localized refinement.
  • Reduced Maximum Error (ME) by at least 25% compared to conventional fixed-step grid search approaches.
  • Decreased Root Mean Square Error (RMSE) and Average Error (AE) by at least 30% relative to fixed-step methods.

Cite This Study

Zhu et al. (2026) studied this question.

synapsesocial.com/papers/6aa0091858e84d0ff5b47c06https://doi.org/10.1002/rcs.70231
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