<p>Soft actuators and sensors are currently used in many industrial applications due to their capability to produce an accurate response. Researchers have studied dielectric electroactive polymers (DEAPs) because these types of structures can be utilized as actuators and as sensors being able to convert electrical energy into mechanical and vice versa. However, production of this kind of structures is complex and in general involve several steps that are time consuming. Customization of these types of structures will be ideal to enhance the performance of the devices based on the specific application. 3D printing technologies have emerged as innovative manufacturing processes that could improve fabrication speed, accuracy, and consistency with low cost. This additive manufacturing technique allows for the possibility of increased device complexity with high versatility. </p> <p>This research studied the potential of 3D printing technologies to produce DEAPs, soft actuators, and flexible sensors. The study presents novel designs of these composite flexible structures, utilizing the most flexible conductive and nonconductive materials available for fused deposition modeling, achieving versatility and high performance in the produced devices. <a>Produced DEAP actuators showed an actuation and electric resistivity higher than other electroactive structures like shape memory alloys and ferroelectric polymers.</a> In addition, this research describes the electromechanical characterization of a flexible thermoplastic polyurethane, (TPU), produced by additive manufacturing, including measurement of the dielectric constant, percentage radial elongation, tensile proprieties, pre-strain effects on actuation, surface topography, and measured actuation under high voltage. DEAP actuators were produced with two different printing paths, concentric circles and lines, showed an area expansion of 4.73% and 5.71% respectively. These structures showed high resistance to electric fields having a voltage breakdown of 4.67 kV and 5.73 kV respectively. <a>Those results are similar to the resistant of the most used dielectric material “VHB 4910”. </a></p> <p>The produced soft pneumatic actuators were successfully 3D printed in one continuous process without support material. The structures were totally sealed without the use of any sealing material or post process. Computational simulations were made to predict the response of the designed structures under different conditions. These results were compared with experimental results finding that the theoretical model is able to predict the response of the printed actuators with an error of less than 7%. This error is satisfactorily small for modeling 3D printed structures and can be further minimized by characterization of the elastomeric material. Besides that, two different grippers were designed based on the opening and closing movements of single bellows actuators. The functionality of both designs was simulated and tested, finding that both designs are capable lifting a heavier rigid structure. </p> <p>Finally, this study presents a computational simulation of a 3D printed flexible sensor, capable of producing an output signal based on the deformation caused by external forces. Two different sensors were designed and tested, working based on a capacitance and resistance change produced by structural deformation. Computational analysis indicate the capacitance sensor should undergo change of capacitance from 3 to 8.5 pF when is exposed to 30 kPa; and the resistance sensor should experience an increase from 101.8 to 103 kΩ when is exposed to 30 kPa. </p>

Current progress in mobility assistive devices revolves around traditional actuation methods including electric motors, hydraulics, and pneumatic cylinders to provide assistive joint torques to the user. While these mechanisms are effective at providing the torques needed, they are often bulky, heavy, and suffer from poor alignment with the joints of the user. These drawbacks have created a need for novel technologies that can provide a more compact and compliant form of actuation. Twisted and coiled polymers, under the thermomechanical class of smart material actuators, have emerged as a strong candidate for use as soft actuators in assistive devices due to their low cost, commercial availability, high stroke capacity, and power density. Progress to their development is currently limited by lack of proper standardization in the fabrication process, along with incomplete characterization of its quasi-static mechanical and thermal behaviours and how the performance is influenced by various design considerations. This thesis defined a fabrication process of twisted coiled polymer actuators and evaluated the trends between design considerations and their impacts on the final actuator performance. In this work, a fabrication rig was developed to manufacture consistent and repeatable actuators, while enabling the control of various identified design parameters. Subsequently, a comprehensive experimental evaluation was accomplished which resulted in a better understanding of the relationships between these parameters and the actuator performance including its tensile stroke, force generation, and variable stiffness properties. The results provided a foundation for designers to consider which variables should be controlled during both actuator fabrication and operation, in order to optimize its final performance to meet a set of prescribed requirements.

A soft quadruped robot is being developed at the Department of Machine Design and Department of Production Engineering at KTH. The legs of the robot consist of four continuum actuators that can achieve complex movements. In order to efficiently develop gaits for the robot, reinforcement learning will be used. The learning process will use data from simulation instead of directly from the real robot to save time and resources. However, it is significantly more computationally expensive to simulate soft robotics than rigid, because the physical laws of flexible materials are inherently complex. Because of this, soft robot simulations tend to be slower which limits their usability for reinforcement learning. This thesis explores simulation modelling options in Matlab Simscape for the soft quadruped robot, that can be used in reinforcement learning. Four simulation models of the soft actuator were implemented in order to be tested and compared. Two actuation methods and two build options were chosen based on the literature study and related works, and were then permuted for the different combinations. The tested combinations are: lumped-parameter method actuated by internal force, flexible beam actuated by internal force, lumped-parameter method actuated by cable/pulley network and flexible beam actuated by cable/pulley network. The four actuators were built and tested separately. Computational time and simulation-to-reality gap were used for evaluating the modeling methods. The results show that the best option when modelling the soft actuator for reinforcement learning in Matlab Simscape is to use the lumped-parameter method in combination with a cable and pulley network. High accuracy level can still be achieved despite not keeping the true number of attachment points between the cable and actuator. The number of pulleys in the model is linearly correlated to the time cost required to simulate the model. / En mjuk fyrbent robot är under utveckling vid institutionen för maskinkonstruktion och institutionen för industriell produktion på KTH. Robotens ben består av fyra kontinuerligt deformerbara ställdon som kan åstadkomma komplexa rörelser. För att effektivt utveckla gångstilar till roboten kommer förstärkt inlärning att användas. Inlärningsprocessen kommer att använda data från simulering istället för från den fysiska roboten för att spara tid och resurser. Det är dock betydligt dyrare beräkningsmässigt att simulera mjuk robotik än styv, eftersom flexibla material är mer komplexa. På grund av detta tenderar simuleringar av mjuka robotar att vara långsammare, vilket begränsar deras användbarhet för förstärkt inlärning. Detta examensarbete utforskar därför alternativ för modellering och simulering av den mjuka fyrbenta roboten i Matlab Simscape, med målet att den ska kunna användas med förstärkt inlärning. Fyra olika simuleringsmodeller av det mjuka ställdonet implementerades för att testas och jämföras. Två aktiveringsmetoder och två konstruktionsalternativ valdes baserat på litteraturstudien och relaterade arbeten, och permuterades sedan till möjliga versioner. De testade versionerna är således: klumpparametermetod som aktiveras av intern kraft, flexibel balk som aktiveras av intern kraft, klumpparametermetod som aktiveras av kabelnätverk och flexibel balk som aktiveras av kabelnätverk. De fyra ställdonen byggdes och testades separat. Beräkningstid och grad av verklighetstrogenhet, användes för att jämföra resultaten av dessa tester. Resultaten visar att det bästa alternativet vid modellering av det mjuka ställdonet för förstärkt inlärning i Matlab Simscape är att använda klumpparametermetoden i kombination med ett kabelnätverk. Hög noggrannhetsnivå kan uppnås trots att man inte bibehåller det verkliga antalet fästpunkter mellan kabeln och ställdonet. Antalet fästpunkter för kabeln i modellen är linjärt korrelerat till den tidskostnad som krävs för att simulera modellen.