• in situ bioprinting
• 3D surface reconstruction
• robotic arm

The aim of the thesis is to design and model a robotic system for in situ bioprinting which is able to recognize and reconstruct the substrate into/onto which print. The robot employed, IMAGObot, has 5 Degrees-of-Freedom (DoF) and was designed in a previous study.
Different scanning technologies were evaluated: contact scanner like a Touch Trigger Probe (TTP), and noncontact scanners such as ultrasonic sensors, a digital camera and structured light.
While the TTP and the ultrasonic sensors were installed on the robotic arm, the other two were tested outside the robotic system.
Each technology was tested on substrates made from different materials with various shapes and mechanical properties. The digital models were reconstructed as triangular meshes and compared with their reference ones to understand the accuracy and the resolution of each device.
By means of the contact scanner with a light sensor (i.e., photoresistor), the substrate can be identified estimating its elastic modulus. The sensor was used to evaluate the indentation depth of the probe while scanning. Assuming the Hertzian contact theory, and so the relation between the applied load and the displacement, the elastic modulus can be found.
The tests were performed on different silicone substrates, showing low percentage errors and values in agreement with those found with the gold standard method (i.e., universal machine testing).
Lastly, the feasibility of the developed scanning system for in situ bioprinting purposes was assessed: the reconstructed models were used to plan the printing path, and then, hydrogels were printed on them. Two different path planning methods were tested: in the first method the extruder follows the surface curvature, while in the second this is kept orthogonal to the robotic platform.
A qualitative analysis was made for each test by comparing the reference pattern with the printed one.
All three main steps - surface scanning, reconstruction/recognition, and path planning - were performed in a Matlab® application, which was previously created but improved/upgraded with more settings and capabilities.