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<p>This study aims at developing a robotic bioprinting system capable of detecting and compensating for unexpected movements or irregularities of the printing substrate in real time, thus achieving high-accuracy deposition. To this end, a fiber-optic distance sensor based on spectral domain optical coherence tomography was integrated on a commercial anthropomorphic 6-axis robot. The sensor provides a continuous signal, which is used in a feedback control system developed in Python. This system dynamically adjusts the position of the end-effector according to the distance from the printing plane, keeping it constant. The entire setup was validated by executing printing tests (planned with simple planar trajectories) on both moving and stationary non-planar substrates with <i>a priori</i> unknown surface geometry. Real-time controlled printing tests proved the functionality of the developed system, showing smooth results in different scenarios while highlighting significant advantages of the proposed approach against procedures without compensation. The end-effector positioning accuracy and the average printed line width deviation resulted lower than 100 <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="170_2025_16810_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="12" /> </InlineMediaObject> <EquationSource Format="TEX">\(\upmu \)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">μ</mi> </math></EquationSource> </InlineEquation>m, thus proving the high compatibility with bioprinting applications. This approach lays the technological foundations for possible future applications of both <i>in situ</i> bioprinting, where physiological movements of the patient, such as breathing, heartbeat or tremors, hinder the accuracy of the deposition, and <i>in vitro</i> bioprinting, where substrates often have surface irregularities that compromise the quality of the final result and used soft materials tend to collapse when considering large size constructs. Moreover, the proposed method guarantees the reduction of the path planning computational cost since it can adapt any printing system to complex surfaces, even when starting from planar trajectories.</p>

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High-accuracy real-time controlled robotic-based bioprinting onto unknown and moving surfaces

  • 期刊论文

  • 发表日期：

    2025年10月20日

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  • Andrea Guerra,
  • Shakiba Davani,
  • Carlo Usai,
  • Tomasz Jüngst,
  • Christos Boutopoulos,
  • Gabriele Maria Fortunato

摘要

This study aims at developing a robotic bioprinting system capable of detecting and compensating for unexpected movements or irregularities of the printing substrate in real time, thus achieving high-accuracy deposition. To this end, a fiber-optic distance sensor based on spectral domain optical coherence tomography was integrated on a commercial anthropomorphic 6-axis robot. The sensor provides a continuous signal, which is used in a feedback control system developed in Python. This system dynamically adjusts the position of the end-effector according to the distance from the printing plane, keeping it constant. The entire setup was validated by executing printing tests (planned with simple planar trajectories) on both moving and stationary non-planar substrates with a priori unknown surface geometry. Real-time controlled printing tests proved the functionality of the developed system, showing smooth results in different scenarios while highlighting significant advantages of the proposed approach against procedures without compensation. The end-effector positioning accuracy and the average printed line width deviation resulted lower than 100 \(\upmu \) μ m, thus proving the high compatibility with bioprinting applications. This approach lays the technological foundations for possible future applications of both in situ bioprinting, where physiological movements of the patient, such as breathing, heartbeat or tremors, hinder the accuracy of the deposition, and in vitro bioprinting, where substrates often have surface irregularities that compromise the quality of the final result and used soft materials tend to collapse when considering large size constructs. Moreover, the proposed method guarantees the reduction of the path planning computational cost since it can adapt any printing system to complex surfaces, even when starting from planar trajectories.