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<p>This study aimed to develop and evaluate a robot-assisted laser osteotomy system that regulates both ablation trajectory and ablation depth through dose–effect model-guided feedforward planning. A Ho:YAG laser delivery and scanning module was integrated with a multi-degree-of-freedom robotic platform, optical navigation, and layered osteotomy planning. Ex vivo porcine femur experiments were performed to establish tissue-specific dose–effect relationship models for cortical and cancellous bone under dynamic scanning conditions. The established models were incorporated into the planning layer to determine the number of ablation layers, scan passes, laser parameters, and robotic scanning trajectories before execution. The system was validated on ex vivo porcine mandible specimens using multiple curved osteotomy paths designed from preoperative CT-based three-dimensional models. Quantitative comparison between the planned and executed ablation geometries showed a mean positional error of 0.85 ± 0.50 mm, a mean angular error of 2.96<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(^\circ\)</EquationSource> </InlineEquation> ± 1.85<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(^\circ\)</EquationSource> </InlineEquation>, and a mean ablation depth error of 0.51 ± 0.50 mm. These results indicate that the proposed feedforward planning strategy can provide predictable trajectory execution and ablation-depth regulation without requiring continuous real-time depth feedback during execution. The proposed system provides an engineering basis for sensing-constrained robot-assisted laser osteotomy, while further validation is required to improve model generalizability and assess its clinical applicability in more complex surgical scenarios.</p> Graphical Abstract <p></p>

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Robot-assisted laser osteotomy system based on dose–effect model-guided feedforward control

  • 期刊论文

  • 发表日期：

    2026年7月7日

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  • Zeng Kuang,
  • Yanping Lin,
  • Shiqi Peng,
  • Yinwei Li,
  • Huifang Zhou

摘要

This study aimed to develop and evaluate a robot-assisted laser osteotomy system that regulates both ablation trajectory and ablation depth through dose–effect model-guided feedforward planning. A Ho:YAG laser delivery and scanning module was integrated with a multi-degree-of-freedom robotic platform, optical navigation, and layered osteotomy planning. Ex vivo porcine femur experiments were performed to establish tissue-specific dose–effect relationship models for cortical and cancellous bone under dynamic scanning conditions. The established models were incorporated into the planning layer to determine the number of ablation layers, scan passes, laser parameters, and robotic scanning trajectories before execution. The system was validated on ex vivo porcine mandible specimens using multiple curved osteotomy paths designed from preoperative CT-based three-dimensional models. Quantitative comparison between the planned and executed ablation geometries showed a mean positional error of 0.85 ± 0.50 mm, a mean angular error of 2.96 \(^\circ\) ± 1.85 \(^\circ\) , and a mean ablation depth error of 0.51 ± 0.50 mm. These results indicate that the proposed feedforward planning strategy can provide predictable trajectory execution and ablation-depth regulation without requiring continuous real-time depth feedback during execution. The proposed system provides an engineering basis for sensing-constrained robot-assisted laser osteotomy, while further validation is required to improve model generalizability and assess its clinical applicability in more complex surgical scenarios.

Graphical Abstract