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- Genre: Doctoral Dissertation
Description
This dissertation introduces and examines Soft Curved Reconfigurable Anisotropic Mechanisms (SCRAMs) as a solution to address actuation, manufacturing, and modeling challenges in the field of soft robotics, with the aim of facilitating the broader implementation of soft robots in various industries. SCRAM systems utilize the curved geometry of thin elastic structures to tackle these challenges in soft robots. SCRAM devices can modify their dynamic behavior by incorporating reconfigurable anisotropic stiffness, thereby enabling tailored locomotion patterns for specific tasks. This approach simplifies the actuation of robots, resulting in lighter, more flexible, cost-effective, and safer soft robotic systems. This dissertation demonstrates the potential of SCRAM devices through several case studies. These studies investigate virtual joints and shape change propagation in tubes, as well as anisotropic dynamic behavior in vibrational soft twisted beams, effectively demonstrating interesting locomotion patterns that are achievable using simple actuation mechanisms. The dissertation also addresses modeling and simulation challenges by introducing a reduced-order modeling approach. This approach enables fast and accurate simulations of soft robots and is compatible with existing rigid body simulators. Additionally, this dissertation investigates the prototyping processes of SCRAM devices and offers a comprehensive framework for the development of these devices. Overall, this dissertation demonstrates the potential of SCRAM devices to overcome actuation, modeling, and manufacturing challenges in soft robotics. The innovative concepts and approaches presented have implications for various industries that require cost-effective, adaptable, and safe robotic systems. SCRAM devices pave the way for the widespread application of soft robots in diverse domains.
ContributorsJiang, Yuhao (Author) / Aukes, Daniel (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Srivastava, Siddharth (Committee member) / Arizona State University (Publisher)
Created2023
Description
Robotic technology can be broadly categorized into two main approaches based on the compliance of the robot's materials and structure: hard and soft. Hard, traditional robots, with mechanisms to transmit forces, provide high degrees of freedom (DoFs) and precise manipulation, making them commonly used in industry and academic research. The field of soft robotics, on the other hand, is a new trend from the past three decades of robotics that uses soft materials such as silicone or textiles as the body or material base instead of the rigid bodies used in traditional robots. Soft robots are typically pre-programmed with specific geometries, and perform well at tasks such as human-robot interaction, locomotion in complex environments, and adaptive reconfiguration to the environment, which reduces the cost of future programming and control. However, full soft robotic systems are often less mobile due to their actuation --pneumatics, high-voltage electricity or magnetics -- even if the robot itself is at a millimeter or centimeter scale. Rigid or hard robots, on the other hand, can often carry the weight of their own power, but with a higher burden of cost for control and sensing. A middle ground is thus sought, to combine soft robotics technologies with rigid robots, by implementing mechanism design principles with soft robots to embed functionalities or utilize soft robots as the actuator on a rigid robotic system towards an affordable robotic system design. This dissertation showcases five examples of this design principle with two main research branches: locomotion and wearable robotics. In the first research case, an example of how a miniature swimming robot can navigate through a granular environment using compliant plates is presented, compared to other robots that change their shape or use high DoF mechanisms. In the second pipeline, mechanism design is implemented using soft robotics concepts in a wearable robot. An origami-inspired, soft "exo-shell", that can change its stiffness on demand, is introduced. As a follow-up to this wearable origami-inspired robot, a geometry-based, ``near" self-locking modular brake is then presented. Finally, upon combining the origami-inspired wearable robot and brake design, a concept of a modular wearable robot is showcased for the purpose of answering a series of biomechanics questions.
ContributorsLi, Dongting (Author) / Aukes, Daniel M (Thesis advisor) / Sugar, Thomas G (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2023
Description
The term Poly-Limb stems from the rare birth defect syndrome, called Polymelia. Although Poly-Limbs in nature have often been nonfunctional, humans have had the fascination of functional Poly-Limbs. Science fiction has led us to believe that having Poly-Limbs leads to augmented manipulation abilities and higher work efficiency. To bring this to life however, requires a synergistic combination between robot manipulation and wearable robotics. Where traditional robots feature precision and speed in constrained environments, the emerging field of soft robotics feature robots that are inherently compliant, lightweight, and cost effective. These features highlight the applicability of soft robotic systems to design personal, collaborative, and wearable systems such as the Soft Poly-Limb.
This dissertation presents the design and development of three actuator classes, made from various soft materials, such as elastomers and fabrics. These materials are initially studied and characterized, leading to actuators capable of various motion capabilities, like bending, twisting, extending, and contracting. These actuators are modeled and optimized, using computational models, in order to achieve the desired articulation and payload capabilities. Using these soft actuators, modular integrated designs are created for functional tasks that require larger degrees of freedom. This work focuses on the development, modeling, and evaluation of these soft robot prototypes.
In the first steps to understand whether humans have the capability of collaborating with a wearable Soft Poly-Limb, multiple versions of the Soft Poly-Limb are developed for assisting daily living tasks. The system is evaluated not only for performance, but also for safety, customizability, and modularity. Efforts were also made to monitor the position and orientation of the Soft Poly-Limbs components through embedded soft sensors and first steps were taken in developing self-powered compo-nents to bring the system out into the world. This work has pushed the boundaries of developing high powered-to-weight soft manipulators that can interact side-by-side with a human user and builds the foundation upon which researchers can investigate whether the brain can support additional limbs and whether these systems can truly allow users to augment their manipulation capabilities to improve their daily lives.
This dissertation presents the design and development of three actuator classes, made from various soft materials, such as elastomers and fabrics. These materials are initially studied and characterized, leading to actuators capable of various motion capabilities, like bending, twisting, extending, and contracting. These actuators are modeled and optimized, using computational models, in order to achieve the desired articulation and payload capabilities. Using these soft actuators, modular integrated designs are created for functional tasks that require larger degrees of freedom. This work focuses on the development, modeling, and evaluation of these soft robot prototypes.
In the first steps to understand whether humans have the capability of collaborating with a wearable Soft Poly-Limb, multiple versions of the Soft Poly-Limb are developed for assisting daily living tasks. The system is evaluated not only for performance, but also for safety, customizability, and modularity. Efforts were also made to monitor the position and orientation of the Soft Poly-Limbs components through embedded soft sensors and first steps were taken in developing self-powered compo-nents to bring the system out into the world. This work has pushed the boundaries of developing high powered-to-weight soft manipulators that can interact side-by-side with a human user and builds the foundation upon which researchers can investigate whether the brain can support additional limbs and whether these systems can truly allow users to augment their manipulation capabilities to improve their daily lives.
ContributorsNguyen, Pham Huy (Author) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas G. (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2020
Description
This dissertation studies the methods to enhance the performance of foldable robots manufactured by laminated techniques. This class of robots are unique in their manufacturing process, which involves cutting and staking up thin layers of different materials with various stiffness. While inheriting the advantages of soft robots -- low weight, affordable manufacturing cost and a fast prototyping process -- a wider range of actuators is available to these mechanisms, while modeling their behavior requires less computational cost.The fundamental question this dissertation strives to answer is how to decode and leverage the effect of material stiffness in these robots. These robots' stiffness is relatively limited due to their slender design, specifically at larger scales. While compliant robots may have inherent advantages such as being safer to work around, this low rigidity makes modeling more complex. This complexity is mostly contained in material deformation since the conventional actuators such as servo motors can be easily leveraged in these robots. As a result, when introduced to real-world environments, efficient modeling and control of these robots are more achievable than conventional soft robots.
Various approaches have been taken to design, model, and control a variety of laminate robot platforms by investigating the effect of material deformation in prototypes while they interact with their working environments. The results obtained show that data-driven approaches such as experimental identification and machine learning techniques are more reliable in modeling and control of these mechanisms. Also, machine learning techniques for training robots in non-ideal experimental setups that encounter the uncertainties of real-world environments can be leveraged to find effective gaits with high performance. Our studies on the effect of stiffness of thin, curved sheets of materials has evolved into introducing a new class of soft elements which we call Soft, Curved, Reconfigurable, Anisotropic Mechanisms (SCRAMs). Like bio-mechanical systems, SCRAMs are capable of re-configuring the stiffness of curved surfaces to enhance their performance and adaptability. Finally, the findings of this thesis show promising opportunities for foldable robots to become an alternative for conventional soft robots since they still offer similar advantages in a fraction of computational expense.
ContributorsSharifzadeh, Mohammad (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
This work presents the design, modeling, analysis, and experimental characterization and testing of soft wearable robotics for lower limb rehabilitation for the ankle and hip. The Soft Robotic Ankle-Foot Orthosis (SR-AFO) is a wearable soft robot designed using multiple pneumatically-powered soft actuators to assist the ankle in multiple degrees-of-freedom during standing and walking tasks. The flat fabric pneumatic artificial muscle (ff-PAM) contracts upon pressurization and assists ankle plantarflexion in the sagittal plane. The Multi-material Actuator for Variable Stiffness (MAVS) aids in supporting ankle inversion/eversion in the frontal plane. Analytical models of the ff-PAM and MAVS were created to understand how the changing of the design parameters affects tensile force generation and stiffness support, respectively. The models were validated by both finite element analysis and experimental characterization using a universal testing machine. A set of human experiments were performed with healthy participants: 1) to measure lateral ankle support during quiet standing, 2) to determine lateral ankle support during walking over compliant surfaces, and 3) to evaluate plantarflexion assistance at push-off during treadmill walking, and 4) determine if the SR-AFO could be used for gait entrainment. Group results revealed increased ankle stiffness during quiet standing with the MAVS active, reduced ankle deflection while walking over compliant surfaces with the MAVS active, and reduced muscle effort from the SOL and GAS during 40 - 60% of the gait cycle with the dual ff-PAM active. The SR-AFO shows promising results in providing lateral ankle support and plantarflexion assistance with healthy participants, and a drastically increased basin of entrainment, which suggests a capability to help restore the gait of impaired users in future trials. The ff-PAM actuators were used in an X-orientation to assist the hip in flexion and extension. The Soft Robotic Hip Exosuit (SR-HExo) was evaluated using the same set of actuators and trials with healthy participants showed reduction in muscle effort during hip flexion and extension to further enhance the study of soft fabric actuators on human gait assistance.
ContributorsThalman, Carly Megan (Author) / Lee, Hyunglae (Thesis advisor) / Artemiadis, Panagiotis (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Soft robots currently rely on additional hardware such as pumps, high voltage supplies,light generation sources, and magnetic field generators for their operation. These components
resist miniaturization; thus, embedding them into small-scale soft robots is challenging.
This issue limits their applications, especially in hyper-redundant mobile robots. This
dissertation aims at addressing some of the challenges associated with creating miniature,
untethered soft robots that can function without any attachment to external power supplies
or receiving any control signals from outside sources. This goal is accomplished by introducing
a soft active material and a manufacturing method that together, facilitate the
miniaturization of soft robots and effectively supports their autonomous, mobile operation
without any connection to outside equipment or human intervention.
The soft active material presented here is a hydrogel based on a polymer called poly(Nisopropylacrylamide)
(PNIPAAm). This hydrogel responds to changes in the temperature
and responds by expanding or contracting. A major challenge regarding PNIPAAm-based
hydrogels is their slow response. This challenge is addressed by introducing a mixedsolvent
photo-polymerization technique that alters the pore structure of the hydrogel and
facilitates the water transport and thus the rate of volume change. Using this technique,
the re-swelling response time of hydrogels is reduced to 2:4min – over 25 times faster
than hydrogels demonstrated previously. The material properties of hydrogels including
their response rate and Young’s modulus are tuned simultaneously. The one-step photopolymerization
using UV light is performed in under 15 sec, which is a significant improvement
over thermo-polymerization, which takes anywhere between a few minutes to
several hours. Photopolymerization is key towards simplifying recipes, improving access
to these techniques, and making them tractable for iterative design processes.
To address the manufacturing challenges, soft voxel actuators (SVAs) are presented.
SVAs are actuated by electrical currents through Joule heating. SVAs weighing only 100 mg require small footprint microcontrollers for their operation which can be embedded
in the robotic system. The advantages of hydrogel-based SVAs are demonstrated through
different robotic platforms namely a hyper-redundant manipulator with 16 SVAs, an untethered
miniature robot for mobile underwater applications using 8 SVAs, and a gripper
using 32 SVAs.
ContributorsKhodambashi, Roozbeh (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Nam, Changho (Committee member) / Arizona State University (Publisher)
Created2021
Description
Soft robotics has garnered attention for its substantial prospective in various domains, such as manipulation and interactions with humans, by offering competitive advantages against rigid robotic systems, including inherent compliance and variable stiffness. Despite these benefits, their theoretically infinite degrees of freedom and prominent nonlinearities pose significant challenges in developing dynamic models and guiding the robots along desired paths. Additionally, soft robots may exhibit rigid behaviors and potentially collide with their surroundings during path tracking tasks, particularly when possible contact points are unknown. In this dissertation, reduced-order models are used to describe the behaviors of three different soft robot designs, including both linear parameter varying (LPV) and augmented rigid robot (ARR) models. While the reduced-order model captures the majority of the soft robot's dynamics, modeling uncertainties notably remain. Non-repeated modeling uncertainties are addressed by categorizing them as a lumped disturbance, employing two methodologies, $H_\infty$ method and nonlinear disturbance observer (NDOB) based sliding mode control, for its rejection. For repeated disturbances, an iterative learning control (ILC) with a P-type learning function is implemented to enhance trajectory tracking efficacy. Furthermore,for non-repeated disturbances, the NDOB facilitates the contact estimation, and its results are jointly used with a switching algorithm to modify the robot trajectories. The stability proof of all controllers and corresponding simulation and experimental results are provided. For a path tracking task of a soft robot with multi-segments, a robust control strategy that combines a LPV model with an innovative improved nonlinear disturbance observer-based adaptive sliding mode control (INASMC). The control framework employs a first-order LPV model for dynamic representation, leverages an improved disturbance observer for accurate disturbance forecasting, and utilizes adaptive sliding mode control to effectively counteract uncertainties. The tracking error under the proposed controller is proven to be asymptotically stable, and the controller's effectiveness is is validated with simulation and experimental results. Ultimately, this research mitigates the inherent uncertainty in soft robot modeling, thereby enhancing their functionality in contact-intensive tasks.
ContributorsQIAO, ZHI (Author) / Zhang, Wenlong (Thesis advisor) / Marvi, Hamidreza (Committee member) / Lee, Hyunglae (Committee member) / Berman, Spring (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023