Surface reconstruction and tissue recognition for robotic-based in situ bioprinting

In this study, an innovative approach for the surface reconstruction and mechanical evaluation of anatomical defects for robotic-based in situ bioprinting applications is presented. A touch probe was developed to be used as the end-effector of a 5 Degrees-of-Freedom robotic arm. The probe, based on the combination of a spring system and a light sensor, is able not only to reconstruct the surface but also to register the penetration depth for each contact point. The knowledge of this parameter allows the evaluation of the mechanical properties of the substrate and thus the recognition of the biological tissue. The probe was able to correctly identify the elastic moduli of silicone substrates with various shapes and stiffnesses (E = 4–23–160 kPa) and showed good agreement compared with standard uniaxial compression test. In situ bioprinting tests were performed onto meshes reconstructed with the probe using different path planning methods. Finally, the presented in situ bioprinting workflow was tested as a proof-of-concept onto an anthropomorphic phantom to completely regenerate a cranial defect. The complete knowledge of the geometry and the mechanical properties of the damaged site allows a more accurate path planning, enabling the deposition of different biomaterials for different target tissues and so the regeneration of heterogeneous anatomical defects. • Robotic-based in situ bioprinting workflow: scanning, localization/registration, path planning, material deposition. • Surface scanning can be performed directly using the robotic arm equipped with a touch probe as end-effector. • A touch probe equipped with a light sensor can be used to evaluate the mechanical properties of the reconstructed substrate. • The knowledge of anatomical defects properties allows a precise path planning for the deposition of different biomaterials.