arXiv subjects

Nick Willemstein

Publications and source records attributed to Nick Willemstein.

4 recordsLinked to original sources

arXiv2025

Pellet-based 3D Printing of Soft Thermoplastic Elastomeric Membranes for Soft Robotic Applications

Additive Manufacturing (AM) is a promising solution for handling the complexity of fabricating soft robots. However, the AM of hyperelastic materials is still challenging with a limited material range. Within this work, pellet-based 3D printing of very soft thermoplastic elastomers (TPEs) was explored (down to Shore Hardness 00-30). Our results show that TPEs can have similar engineering stress and maximum elongation as Ecoflex OO-10. In addition, we 3D-printed airtight thin membranes (0.2-1.2 mm), which could inflate up to a stretch of 1320%. Combining the membrane's large expansion and softness with the 3D printing of hollow structures simplified the design of a bending actuator that can bend 180 degrees and reach a blocked force of 238 times its weight. In addition, by 3D printing TPE pellets and rigid filaments, the soft membrane could grasp objects by enveloping an object or as a sensorized sucker, which relied on the TPE's softness to conform to the object or act as a seal. In addition, the membrane of the sucker acted as a tactile sensor to detect an object before adhesion. These results suggest the feasibility of AM of soft robots using soft TPEs and membranes as a promising class of materials and sensorized actuators, respectively.

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arXiv2023

3D Printed Proprioceptive Soft Fluidic Actuators with Graded Porosity

Integration of both actuation and proprioception into the robot body would provide actuation and sensing in a single integrated system. Within this work, a manufacturing approach for such actuators is investigated that relies on 3D printing for fabricating soft-graded porous actuators with piezoresistive sensing and identified models for strain estimation. By 3D printing, a graded porous structure consisting of a conductive thermoplastic elastomer both mechanical programming for actuation and piezoresistive sensing were realized. Whereas identified Wiener-Hammerstein (WH) models estimate the strain by compensating the nonlinear hysteresis of the sensorized actuator. Three actuator types were investigated, namely: a bending actuator, a contractor, and a three DoF bending segment (3DoF). The porosity of the contractors was shown to enable the tailoring of both the stroke and resistance change. Furthermore, the WH models could provide strain estimation with on average high fits (83%) and low RMS errors (6%) for all three actuators, which outperformed linear models significantly (76.2/9.4% fit/RMS error). These results indicate that an integrated manufacturing approach with both 3D printed graded porous structures and system identification can realize sensorized actuators that can be tailored through porosity for both actuation and sensing behavior but also compensate for the nonlinear hysteresis.

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arXiv2023

Soft insoles for estimating 3D ground reaction forces using 3D printed foam-like sensors

Sensorized insoles provide a tool for gait studies and health monitoring during daily life. For users to accept such insoles they need to be comfortable and lightweight. Previous work has already demonstrated that estimation of ground reaction forces (GRFs) is possible with insoles. However, these are often assemblies of commercial components restricting design freedom and customization. Within this work, we investigate using four 3D-printed soft foam-like sensors to sensorize an insole. These sensors were combined with system identification of Hammerstein-Wiener models to estimate the 3D GRFs, which were compared to values from an instrumented treadmill as the golden standard. It was observed that the four sensors behaved in line with the expected change in pressure distribution during the gait cycle. In addition, the identified (personalized) Hammerstein-Wiener models showed the best estimation performance (on average RMS error 9.3%, R^2=0.85 and mean absolute error (MAE) 7%) of the vertical, mediolateral, and anteroposterior GRFs. Thereby showing that these sensors can estimate the resulting 3D force reasonably well. These results for nine participants were comparable to or outperformed other works that used commercial FSRs with machine learning. The identified models did decrease in estimation performance over time but stayed on average 11.35% RMS and 8.6% MAE after a week with the Hammerstein-Wiener model seeming consistent between days two and seven. These results show promise for using 3D-printed soft piezoresistive foam-like sensors with system identification to be a viable approach for applications that require softness, lightweight, and customization such as wearable (force) sensors.

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arXiv2022

Direct 3D Printing of Soft Fluidic Actuators with Graded Porosity

New additive manufacturing methods are needed to realize more complex soft robots. One example is soft fluidic robotics, which exploits fluidic power and stiffness gradients. Porous structures are an interesting type for this approach, as they are flexible and allow for fluid transport. Within this work, the Infill-Foam (InFoam) is proposed to print structures with graded porosity by liquid rope coiling (LRC). By exploiting LRC, the InFoam method could exploit the repeatable coiling patterns to print structures. To this end, only the characterization of the relation between nozzle height and coil radius and the extruded length were necessary (at a fixed temperature). Then by adjusting the nozzle height and/or extrusion speed the porosity of the printed structure could be set. The InFoam method was demonstrated by printing porous structures using styrene-ethylene-butylene-styrene (SEBS) with porosities ranging from 46\% to 89\%. In compression tests, the cubes showed large changes in modulus (more than 200 times), density (-89\% compared to bulk), and energy dissipation. The InFoam method combined coiling and normal plotting to realize a large range of porosity gradients. This grading was exploited to realize rectangular structures with varying deformation patterns, which included twisting, contraction, and bending. Furthermore, the InFoam method was shown to be capable of programming the behavior of bending actuators by varying the porosity. Both the output force and stroke showed correlations similar to those of the cubes. Thus, the InFoam method can fabricate and program the mechanical behavior of a soft fluidic (porous) actuator by grading porosity.

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