Geometry-based customization of bending modalities for 3D-printed soft pneumatic actuators

In this work, we propose a novel type of 3D-printed soft pneumatic actuator that allows geometry-based customization of bending modalities. While motion in the 3D-space has been achieved for several types of soft actuators, only 2D-bending has been previously modelled and characterized within the scope of 3D-printed soft pneumatic actuators. We developed the first type of 3D-printed soft pneumatic actuator which, by means of the unique feature of customizable cubes at an angle with the longitudinal axis of the structure, is capable of helical motion. Thus, we characterize its mechanical behavior and formulate mathematical and FEA models to validate the experimental results. Variation to the pattern of the inclination angle along the actuator is then demonstrated to allow for complex 3D-bending modalities and the main applications in the fields of object manipulation and wearable robotics are finally discussed

Effect of mechanical parameters on dielectric elastomer minimum energy structures

Soft robotics may provide many advantages compared to traditional robotics approaches based on rigid materials, such as intrinsically safe physical human-robot interaction, efficient/stable locomotion, adaptive morphology, etc. The objective of this study is to develop a compliant structural actuator for soft a soft robot using dielectric elastomer minimum energy structures (DEMES). DEMES consist of a pre-stretched dielectric elastomer actuator (DEA) bonded to an initially planar flexible frame, which deforms into an out-of-plane shape which allows for large actuation stroke. Our initial goal is a one-dimensional bending actuator with 90 degree stroke. Along with frame shape, the actuation performance of DEMES depends on mechanical parameters such as thickness of the materials and pre-stretch of the elastomer membrane. We report here the characterization results on the effect of mechanical parameters on the actuator performance. The tested devices use a cm-size flexible-PCB (polyimide, 50 μm thickness) as the frame-material. For the DEA, PDMS (approximately 50 μm thickness) and carbon black mixed with silicone were used as membrane and electrode, respectively. The actuators were characterized by measuring the tip angle and the blocking force as functions of applied voltage. Different pre-stretch methods (uniaxial, biaxial and their ratio), and frame geometries (rectangular with different width, triangular and circular) were used. In order to compare actuators with different geometries, the same electrode area was used in all the devices. The results showed that the initial tip angle scales inversely with the frame width, the actuation stroke and the blocking force are inversely related (leading to an interesting design trade-off), using anisotropic pre-stretch increased the actuation stroke and the initial bending angle, and the circular frame shape exhibited the highest actuation performance

Finite element modeling of dielectric elastomer actuators for space applications

A special actuator device with passive sensing capability based on dielectric elastomer was studied and specialized to be used in space applications. The work illustrates the research project modeling procedure adopted to simulate the mechanical behavior of this material based on a finite element theory approach. The Mooney-Rivlin’s hyperelastic and Maxwell’s electrostatic models provide the theoretical basis to describe its electro-mechanic behavior. The validation of the procedure is performed through a numerical-experimental correlation between the response of a prototype of actuator developed by the Risø Danish research center and the 3D finite element model simulations. An investigation concerning a possible application in the space environment of dielectric elastomer actuators (DEA) is also presented

Comparison of DC Motors and Dielectric Elastomer Actuators For Wearable Wrist Exoskeletons

Paralysis or loss of strength resulting from stroke requires patients to undergo extensive rehabilitation therapy. It is known that intensive therapy contributes significantly to recovery, but as the number of surviving stroke patients increases, it is difficult for clinics to provide patients with the optimal level of therapy. Robotic devices for wrist rehabilitation have been developed to lessen these problems, but at the moment they are physically large and must be used within a clinical setting. More benefit could be obtained if the devices were portable, so that they could be used by the patients on a daily basis. To reduce the size of these devices, other means of actuation need to be considered, as currently DC motors and the required transmission are too large and heavy. Dielectric elastomer actuators (DEAs) may provide a solution to the actuation problem. The focus of this thesis was to compare DC motors with DEAs for use in a wearable wrist exoskeleton to assist with stroke rehabilitation. A simple setup of the forearm, wrist, and hand was developed for testing DC motors and DEAs. For testing the DC motors, kinematic and dynamic models of the arm were created to develop an inverse dynamics controller used to control the movement of the hand. DEAs were fabricated and tested to determine their capabilities in terms of force and range of motion. Based on the data collected, an electromechanical model was optimized to characterize the behavior of the DEAs. The results show that a single DEA strip is not capable of providing the force or range of motion required for a wearable wrist exoskeleton. Future work can be done to improve DEA design so that they may actuate a wearable wrist exoskeleton or could also be considered for use in other wearable rehabilitation devices

3D-Printing and Machine Learning Control of Soft Ionic Polymer-Metal Composite Actuators

This paper presents a new manufacturing and control paradigm for developing soft ionic polymer-metal composite (IPMC) actuators for soft robotics applications. First, an additive manufacturing method that exploits the fused-filament (3D printing) process is described to overcome challenges with existing methods of creating custom-shaped IPMC actuators. By working with ionomeric precursor material, the 3D-printing process enables the creation of 3D monolithic IPMC devices where ultimately integrated sensors and actuators can be achieved. Second, Bayesian optimization is used as a learning-based control approach to help mitigate complex time-varying dynamic effects in 3D-printed actuators. This approach overcomes the challenges with existing methods where complex models or continuous sensor feedback are needed. The manufacturing and control paradigm is applied to create and control the behavior of example actuators, and subsequently the actuator components are combined to create an example modular reconfigurable IPMC soft crawling robot to demonstrate feasibility. Two hypotheses related to the effectiveness of the machine-learning process are tested. Results show enhancement of actuator performance through machine learning, and the proof-of-concepts can be leveraged for continued advancement of more complex IPMC devices. Emerging challenges are also highlighted

Design of a pneumatic soft robotic actuator using model-based optimization

In this thesis, the design and optimization process of a novel soft intelligent modular pad (IntelliPad) for the purpose of pressure injury prevention is presented. The structure of the IntelliPad consists of multiple individual multi-chamber soft pneumatic-driven actuators that use pressurized air and vacuum. Each actuator is able to provide both vertical and horizontal motions that can be controlled independently. An analytical modeling approach using multiple cantilever beams and virtual springs connected in a closed formed structure was developed to analyze the mechanical performance of the actuator. The analytical approach was validated by a finite element analysis. For optimizing the actuator\u27s mechanical performance, firefly algorithm and deep reinforcement learning-based design optimization frameworks were developed with the purpose of maximizing the horizontal motion of the top surface of the actuators, while minimizing its corresponding effect on the vertical motion. Four optimized designs were fabricated. The actuators were tested and validated experimentally to demonstrate their required mechanical performance in order to regulate normal and shear stresses at the skin-pad interface for pressure injury prevention applications

Robotic Actuation and Control with Programmable, Field-Activated Material Systems

This dissertation presents novel, field-activated smart material systems for the actuation and control of autonomous robots. Smart materials, a type of material whose properties can be changed with an external stimuli, represent a promising direction to expand upon existing robotic control and actuation methods, particularly in the sub-fields of soft robotics and robotic grasping. Specifically, this work makes the following contributions: i) a literature review that synthesizes recent work on field-activated smart materials and their use in soft robotics; ii) an electrorheological fluid (ERF) valve to control soft actuators; iii) magnetic elastomers (MEs) to increase the grip strength of soft grippers; and iv) a low-power method for torque transmission enabled by magnetorheological fluid (MRF) and electropermanent magnet arrays. After the introduction, this dissertation presents a comprehensive literature review paper (Chapter 2) regarding the use of field-activated materials in soft robotics, with an emphasis on magnetic elastomers. The second paper (Chapter 3) describes the development of a 3D-printed pressure valve intended to leverage the pressuring-holding properties of ERF when under the influence of a high voltage field to actuate soft actuators. The third paper (Chapter 4) demonstrates how magnetic elastomers and magnetic fields can enhance soft robotic grip strength and versatility. The fourth paper (Chapter 5) models, fabricates, and characterizes a MRF-containing clutch device able to rapidly and reversibly module the amount of torque transmitted from an input shaft to an output by leveraging low-power electropermanent magnet arrays. Each work focuses on a field-activated smart material to perform a specific robotic function, with particular emphasis given to compliant mechanisms and soft robotics, as well as to reducing cost and improving ease of fabrication with the use of modern fabrication techniques. In these described papers, field-activated materials are first modeled and then deployed in functional prototypes, and their robotic utility is described in detail after extensive experimental characterization

High Efficiency Real-Time Sensor and Actuator Control and Data Processing

The advances in sensor and actuator technology foster the use of large multitransducer networks in many different fields. The increasing complexity of such networks poses problems in data processing, especially when high-efficiency is required for real-time applications. In fact, multi-transducer data processing usually consists of interconnection and co-operation of several modules devoted to process different tasks. Multi-transducer network modules often include tasks such as control, data acquisition, data filtering interfaces, feature selection and pattern analysis. Heterogeneous techniques derived from chemometrics, neural networks, fuzzy-rules used to implement such tasks may introduce module interconnection and co-operation issues. To help dealing with these problems the author here presents a software library architecture for a dynamic and efficient management of multi-transducer data processing and control techniques. The framework’s base architecture and the implementation details of several extensions are described. Starting from the base models available in the framework core dedicated models for control processes and neural network tools have been derived. The Facial Automaton for Conveying Emotion (FACE) has been used as a test field for the control architecture