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

IF 2.4 3区医学 Q2 SURGERY

International Journal of Medical Robotics and Computer Assisted Surgery Pub Date : 2026-09-06 DOI:10.1002/rcs.70231

Yinzhi Zhu, Hongbing Li

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引用次数: 0

Abstract

Background

Reliable force perception is critical in robot-assisted minimally invasive surgery. However, constraints in end-effector size and complexity of the surgical environment hamper the integration of force sensors for direct feedback.

Methods

In this study, an adaptive grid search algorithm with dynamic step-size adjustment is proposed to optimise the Hunt–Crossley (HC) model parameters for precise force estimation in robotic applications. The method continuously adjusts the step size based on real-time estimation error, thereby enabling efficient investigation of the parameter space and refined optimisation near the optimal solution.

Results

Experimental results show that the proposed method improves force estimation accuracy, with a reduction in Maximum Error (ME) of at least 25%, and reductions in Root Mean Square Error (RMSE) and Average Error (AE) of at least 30% compared to conventional fixed-step approaches.

Conclusions

These improvements enhance operational safety and also achieve the balance between computational efficiency and perception accuracy.

查看原文本刊更多论文

基于动态步长调整的机器人-组织相互作用力估计自适应网格搜索方法。

背景：可靠的力感知是机器人辅助微创手术的关键。然而，末端执行器尺寸的限制和手术环境的复杂性阻碍了力传感器的直接反馈集成。方法：提出了一种动态步长调整的自适应网格搜索算法，对机器人应用中的Hunt-Crossley （HC）模型参数进行优化，以实现精确的力估计。该方法基于实时估计误差不断调整步长，从而能够有效地研究参数空间并在最优解附近进行精细优化。结果：实验结果表明，与传统的固定步长方法相比，该方法提高了力估计精度，最大误差（ME）降低了至少25%，均方根误差（RMSE）和平均误差（AE）降低了至少30%。结论：这些改进提高了操作安全性，也实现了计算效率和感知精度之间的平衡。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Medical Robotics and Computer Assisted Surgery 医学-外科

CiteScore

4.50

自引率

12.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.