Browsing by Author "Becker, Aaron T."
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Item A Heterogeneous Robotics Team for Large-Scale Seismic Sensing(IEEE Robotics and Automation Letters, 2/8/2017) Sudarshan, Srikanth K. V.; Montano, Victor; Nguyen, An; McClimans, Michael; Chang, Li; Stewart, Robert R.; Becker, Aaron T.Seismic surveying requires placing a large number of sensors (geophones) in a grid pattern, triggering a seismic event, and recording vibration readings. The goal of the surveying is often to locate subsurface resources. Traditional seismic surveying employs human laborers for sensor placement and retrieval. The major drawbacks of surveying with human deployment are the high costs and time, and risks to humans due to explosives, terrain, and climatic conditions. We propose an autonomous, heterogeneous sensor deployment system using unmanned aerial vehicles to deploy mobile and immobile sensors. The proposed system begins to overcome some of the problems associated with traditional systems. This paper provides detailed analysis and comparison with traditional survey techniques. Hardware experiments and simulations show promise for automation reducing cost and time. Autonomous aerial systems will have a substantial contribution to make in future seismic surveys.Item A Magnetic Manipulator Cooled With Liquid Nitrogen(IEEE Robotics and Automation Letters, 8/6/2018) Isichei, Benedict; Becker, Aaron T.; Leclerc, JulienMiniature robots manipulated by external magnetic fields could enable less invasive surgeries. Magnetic tools, capsules, or medication can be controlled inside a human body using electromagnets. However, resistive magnetic devices able to produce strong magnetic fields in a large volume inefficiently use space and energy. This letter presents the design and testing of a magnetic manipulator cooled with liquid nitrogen. This technique reduces the electrical resistance of copper wires. It, therefore, reduces the amount of heat generated to produce a given magnetic field. Liquid nitrogen-cooled electromagnets are smaller than air-cooled ones and use less power. This letter examines how both effects scale with the size of the workspace. The system presented possesses six electromagnets and its ability to control a robot is demonstrated experimentally.Item A Novel Robotic Surveying Technique for Free-Falling Penetrometers(2020-05) Akinwande, Samuel I.Severe floods and sea level rise (SLR) are increasingly urgent effects of global climate change. Wetlands are natural buffers that prevent inundation and destruction from floods. Anthropogenic destruction of wetlands is reducing their effectiveness as flood buffers. Rapid and timely assessment methods are needed for the effective restoration of the wetlands. This thesis presents a novel method for performing free falling penetrometer (FFP) tests for soft wetland soils. The method involves the aerial deployment of a custom FFP using a consumer quadcopter. The method was tested in three soils to examine the effect of drop height on the FFP deceleration profile and penetration depth. Further tests were conducted to determine the force required to extract the FFP after a successful drop. The effects of speed and angle on extraction force was analyzed. Field tests were simulated by conducting limited indoor surveys with the FFP and a consumer drone. The custom FFP was successful in distinguishing wetland soils in drop experiments. The relationships between drop height, penetration depth and deceleration profile were characterized. Data from extraction tests revealed a linear relationship between extraction force and speed; and an inverse relationship between extraction force and angle. By utilizing techniques to minimize the extraction force, a consumer drone was successful in deploying and retrieving the custom FFP. Further field tests are needed to validate the robustness of the novel method. If proven reliable, this method will be useful in reducing the financial and labor costs associated with wetlands surveys.Item A Novel Transmission Mechanism for MRI-Compatible Surgery Robot(2017-12) Liu, Xin 1976-; Tsekos, Nikolaos V.; Becker, Aaron T.; Chen, Guoning; Shi, WeidongMinimally invasive surgery (MIS) techniques provide reduced patient discomfort, faster healing time, decreased risk of complications, and better overall patient outcomes. Medical imaging guidance is particularly crucial for MIS in which the procedure is performed through small openings in the body which resulting in limited sensory information available to surgeon compared with the open approach. Magnetic Resonance Imaging (MRI) is an intrinsically three-dimensional (3D) modality which offers high contrast and spatial resolution and a plethora of soft-tissue contrast mechanisms for assessment of anatomical morphology and function. These benefit , in addition to the fact that it does not require ionizing radiation, makes it a desirable methodology for image-guided interventions (IGI). An impediment to those advancements, however, is the limited access to patients, especially to the high-fi eld cylindrical magnetic resonance (MR) scanners. To address the limited accessibility and facilitate real-time guidance of interventions, remotely actuated and controlled MRI-compatible manipulators have been introduced. The MRI compatible interventional systems require appropriate forms of actuation. The commonly used electromagnetic actuators by many robotic system, like surgical robots, are, in general, not compatible with the MRI environment owing to their magnetically susceptible materials and electromagnetic components which are MR unsafe. In this work, we propose a novel transmission mechanism, herein referred to as Solid-Media Transmission (SMT), to transmit force from MR unsafe components located outside of the MR environment to the end effectors which are MR safe or MR conditional. We focus on the design, fabrication and control of a SMT-based actuator and an integrated robotic system that are aimed to perform the task of a surgical tool or needle placement. Experimental studies have demonstrated the feasibility and characteristics of the SMT and SMT-enabled devices for MRI guided intervention.Item Achieving Commutation Control of an MRI-powered Robot Actuator(IEEE Transactions on Robotics, 3/16/2015) Felfoul, Ouajdi; Becker, Aaron T.; Bergeles, Christos; Dupont, Pierre E.Actuators that are powered, imaged, and controlled by magnetic resonance (MR) scanners could inexpensively provide wireless control of MR-guided robots. Similar to traditional electric motors, the MR scanner acts as the stator and generates propulsive torques on an actuator rotor containing one or more ferrous particles. Generating maximum motor torque while avoiding instabilities and slippage requires closed-loop control of the electromagnetic field gradients, i.e., commutation. Accurately estimating the position and velocity of the rotor is essential for high-speed control, which is a challenge due to the low refresh rate and high latency associated with MR signal acquisition. This paper proposes and demonstrates a method for closed-loop commutation based on interleaving pulse sequences for rotor imaging and rotor propulsion. This approach is shown to increase motor torque and velocity, eliminate rotor slip, and enable regulation of rotor angle. Experiments with a closed-loop MR imaging actuator produced a maximum force of 9.4 N.Item Algorithms for Particle Swarms Using Global Control: Aggregation, Mapping, Coverage, Foraging, and Shape Control(2017-05) Viswanathan Mahadev, Arun; Becker, Aaron T.; Tsekos, Nikolaos V.; Pan, MiaoTargeted drug delivery is a promising technique to reduce the side effects of drugs by delivering them in concentrated doses using large swarms (10^16) of controllable microbots only targeting bad or infected tissue. A promising way to control small steerable microbots is by using a global control field such as the magnetic gradient of an MRI machine. In this work we develop benchmark algorithms for performing aggregation of microbots using global control. Using our findings we develop algorithms for a novel approach of mapping tissue and vascular systems without the use of harmful contrast agents in an MRI. In our work we consider a swarm of particles in a 1D, 2D, and 3D grids that can be tracked and controlled by an external agent thus building a map. We present algorithms for controlling particles using global inputs to perform: (1) Mapping, i.e., building a representation of the free and obstacle regions of the workspace; (2) Foraging, i.e., ensuring that at least one particle reaches each target location;and (3) Coverage, i.e., ensuring that every free region on the map is visited by at least one particle. Finally we also demonstrate shape control of large swarms using global control by developing an algorithm for position control.Item Applications of Unmanned Vehicles with Wireless Sensor Networks and Surveying(2018-12) Nguyen, An Vn; Becker, Aaron T.; Franchek, Matthew A.; Pan, MiaoAn unmanned vehicle, such as a flying multi-copter, an unmanned rover, a remote-controlled boat, can be used to cover a large area of land, to perform repetitive, tedious yet strenuous tasks for people. We can have an unmanned aerial vehicle (UAV) distribute a network of seismic microphone, used during seismic surveying, in treacherous terrain, free of heavy signal wiring, without risking injury to human workers. A UAV can sweep a large area with a mosquito-zapping net, destructively sampling mosquito population in the area, giving entomology researcher better data about their distribution and behavior through time and space. An unmanned boat, or a UAV, can distribute a drifting wireless sensor network (WSN) into a body of water. The same, or several unmanned vehicles, can then monitor, recharge and finally recollect them. The following thesis presents hardware for all of the above applications, as well as software and algorithms for the unmanned vehicles, and sensor nodes.Item Approximate Steering of a Unicycle Under Bounded Model Perturbation Using Ensemble Control(IEEE Transactions on Robotics, 2/24/2012) Becker, Aaron T.; Bretl, Timothy W.This paper considers the problem of steering a nonholonomic unicycle despite model perturbation that scales both the forward speed and the turning rate by an unknown but bounded constant. We model the unicycle as an ensemble control system, show that this system is ensemble controllable, and derive an approximate steering algorithm that brings the unicycle to within an arbitrarily small neighborhood of any given Cartesian position. We apply our work to a differential-drive robot with unknown but bounded wheel radius and validate our approach with hardware experiments.Item Automating a Seismic Survey Using Heterogenous Sensor Teams and Unmanned Aerial Vehicles(2016-12) Venkata Sudarshan, Srikanth; Becker, Aaron T.; Stewart, Robert R.; Pan, Miao; Han, ZhuSeismic imaging is the primary technique for subsurface exploration. It requires placing a large number of sensors (geophones) in a grid pattern, triggering a seismic event, and recording the propagating waves. The location of hydrocarbons is inferred from these readings. Traditional seismic surveying for hydrocarbons employs human laborers for sensor placement, lays miles of cabling, and then recovers the sensors. Often sites of resource or rescue interest may be difficult or hazardous to access. The major drawbacks of surveying with human deployment are the high costs and time, and risks to humans due to explosives and harsh climatic conditions. Thus, there is a substantial need to automate the process of seismic sensor placement and retrievals using robots. We propose an autonomous, heterogeneous sensor deployment system using UAVs to plant immobile sensors and deploy mobile sensors. Detailed analysis and comparison with traditional surveying were conducted. Hardware experiments and simulations prove the effectiveness of automation regarding cost and time. The proposed system overcame the drawbacks and displayed higher efficiency. The deployed sensors essentially became a wireless sensor network (WSN). Thus traditional batteries cannot sustain a WSN. Energy is the major impediment to the sustainability of WSNs. Most energy is consumed by (i) wireless transmissions of sensed data and (ii) long-distance multi-hop transmissions from the source sensors to the sink. This research also presents an optimal path-planning algorithm for sustaining WSNs and validates the claim with simulations. The research in the future aims at exploring methods to exploit emerging wireless power transfer technology by using UAVs to service the WSNs. These UAVs cut data transmissions from long to short distances by collecting sensed information and replenishing WSN’s energy.Item Brain Machine Interface with Closed-Loop Neuromuscular Stimulation for Grasping in Stroke and Spinal Cord Injury Survivors(2017-12) Bhagat, Nikunj Arunkumar; Contreras-Vidal, Jose L.; Becker, Aaron T.; Thrasher, Timothy Adam; Francisco, Gerard E.; Ogmen, HalukSixty percent of elderly hand movements involve grasping, which is unarguably why grasp restoration is a major component of upper-limb rehabilitation therapy. Neuromuscular, or functional electrical stimulation (FES), can help retrain grasping by using short bursts of electrical pulses to artificially contract paralyzed muscles. However, current home-use FES requires users to operate a keypad or coordinate body movements for initiating the stimulation, which is often challenging and inefficient for paralyzed patients, as well as unfeasible for severely impaired patients. Conversely, therapeutic FES devices that are controlled by a therapist or pre-programmed, fail to engage patients and ultimately undermine the therapy outcomes. Besides, commercially available FES devices are open-loop systems that require frequent parameter adjustments, which disrupts their continuous use. To increase engagement and ensure accessibility to severely impaired patients, several researchers have suggested non-invasive electroencephalography (EEG)-based brain-machine interfaces (BMI) that allow patients to operate FES devices using their brain activity. However, EEG’s weak signal-to-noise ratio and inherent trial-to-trial variability, have deteriorated the performance of EEG-based BMIs and compromised their long-term reliability. Likewise, closed-loop FES for grasping is promising, but its long-term efficacy is debatable due to lack of effective muscle models, subject variability, and implementation challenges. To address EEG’s challenges, we developed a novel BMI design using optimal adaptive windows to extract movement related cortical potentials, which is a widely studied neural correlate of movement intention. A pilot study with four chronic stroke survivors demonstrated consistent above chance-level BMI performance (65% true and 28% false positives) across two days. In a subsequent study involving two stroke, one spinal injury, and two control subjects, we evaluated the efficacy of integrating BMI with closed-loop FES in order to restore grasping. A custom-built FES prototype using feedback control was developed to automatically adjust the stimulation intensities during grasping and was further validated in an isometric force tracking task. After three sessions, it was concluded that the normalized tracking errors were significantly smaller during closed-loop stimulation (25 ± 15%) versus open-loop stimulation (31 ± 24%), (F (748.03, 1) = 23.22, p < 0.001). These findings will benefit future designs of BMI with closed-loop FES and help determine the clinical efficacy of BMI-FES therapy in motor rehabilitation, following stroke or spinal cord injury.Item Building Structures with a Swarm of Robots(2018-10-18) Ike, RhemaAdvances in construction automation have primarily focused on creating heavy machines to accomplish repetitive tasks. While this approach is valuable in an assembly-line context, it does not always translate well for the tight confines and dynamic nature of construction sites. To address the challenges of construction-site assembly, this project suggests an alternative technique that uses a fleet of smaller robots working collaboratively. Instead of using complex robot manipulators and simple building materials, we embed most of the complexity in the build modules. In our tests, we used cardstock that could pop-up from its 2D form into a 3D brick. Curved creases were laser-scored into the cardstock to encourage it to take a 3D form when the robots applied forces to it at certain points. The proposed method has potential advantages over large machines and simple build materials. It enables task-assignment flexibility and portability. Scaling the operation can be accomplished by adding or removing additional units as needed. The use of assembly robots also opens new horizons for design creativity, allowing architects to explore new ideas that would be unwieldy and expensive to construct using traditional techniques. Our proof-of-concept used a fleet of five Cozmo robots. Each Cozmo weighs 180 grams and has a 3D printed forklift attached to its lift. The Cozmos work collaboratively to popup-construct 3D bricks and assemble them into a chain.Item Closed-Loop Control of Mesoscale Magnetic Robots Using a Global Magnetic Field(2023-05-11) Lu, Yitong; Becker, Aaron T.; Faghih, Rose T.; Mayerich, David; Kim, MinJun; Ruchhoeft, Paul; Leclerc, JulienThis dissertation investigates three types of mesoscale (milli- and microscale) magnetic robots: magnetic swimmers, magnetic modular cubes, and ferromagnetic micro-particles. Mesoscale magnetic robots show great potential for revolutionizing many aspects of medical and clinical applications. The dissertation investigates Millimeter-scale Magnetic Rotating Swimmers (MMRSs) that could be used to improve surgical procedures. An external rotating magnetic field produces a torque on the swimmers to make them rotate. MMRSs have propeller fins that convert the rotating motion into forward propulsion. The dissertation reports on optimization studies for the MMRS designs and control techniques used experimentally to remove thrombi from a bifurcating vascular model. The dissertation also presents data-driven models to improve MMRS’s 3D path-following performance of a time-delayed sensing system. An algorithm for 2.5D closed-loop control of the MMRS using only 2D ultrasound feedback is proposed and tested experimentally. In addition, a preliminary study of the biocompatibility of the MMRSs is presented. Magnetic Modular Cubes (MMCs) are scalable modular subunits with embedded permanent magnets in a 3D-printed cubic body. Due to the MMC’s cubic design, magnetically connected structures of MMCs are polyominoes in 2D and polycubes in 3D. MMCs represent progress toward a mesoscale manufacturing method controllable by an external force field that combines the precision of modules, the reusability of Legos, and the self-assembly of DNA. The dissertation provides a family of designs of MMCs and a 2D low-fidelity motion planner that computes all reachable polyomino shapes (and their shortest movement sequences) from an arbitrary initial configuration. A closed-loop control method is presented for self-assembling the MMCs in 2D using computer vision-based feedback with re-planning techniques. Furthermore, methods to enumerate polyominoes and polycubes are presented. For biomedical applications in targeted therapy delivery and interventions, a large swarm of micro-scale particles has to be moved through a maze-like environment to a target region. The dissertation demonstrates how to use a time-varying magnetic field to gather ferromagnetic micro-particles to a desired location using reinforcement learning. In addition, methods to overcome the simulation-to-reality gap are explained in the dissertation.Item Computational Methods for MRI-Guided and Powered Ferric Applicators: Modeling and Image Processing(2021-12) Chu, Wenhui; Tsekos, Nikolaos V.; Shi, Weidong; Eick, Christoph F.; Becker, Aaron T.Cardiac diseases are major causes of global mortality which are a consistent threat to the lives of people. With the development of left ventricle segmentation, the real-time MRI-based control of a ferromagnetic application for endovascular navigation with data sensing and feedback in cardiac was applied in recent years. In this work, we first propose three novel deep learning architectures called BNU-net, LNU-net, and IBU-net for left ventricle segmentation from short-axis cine MRI images. BNU-net is the batch normalized (BN) U-net, LNU-net is the layer normalized (LN) U-net, and IBU-net is the instance-batch normalized (IB) U-net. The architectures of BNU-net, LNU-net, and IBU-net have an encoding path for feature extraction and a decoding path that enables precise localization. BNU-net, LNU-net, and IBU-net have left ventricle segmentation methods: BNU-net employs batch normalization to the results of each convolutional layer, LNU-net applies layer normalization in each convolutional block, while IBU-net incorporates instance and batch normalization together in the first convolutional block. Our method incorporates affine transformations and elastic deformations for image data processing. Our dataset that contains 805 MRI images regarding the left ventricle from 45 patients is used for evaluation. The experimental results reveal that our approach accomplishes comparable or better performance than other state-of-the-art approaches in terms of the dice coefficient and the average perpendicular distance. We then simulate a computational platform for preoperative planning and modeling of MRI-powered applicators inside blood vessels. This platform was implemented as a two-way data and command pipeline that links the MRI scanner, the computational core, and the operator. The platform first processes multi-slice MR data to extract the vascular bed and then fits a virtual corridor inside the vessel. This corridor serves as a virtual fixture (VF), a forbidden region for the applicators to avoid vessel perforation or collision. The geometric features of the vessel centerline, the VF, and MRI safety compliance (dB/dt, max available gradient) are then used to generate magnetic field gradient waveforms. Different blood flow profiles can be user-selected, and those parameters are used for modeling the applicator's maneuvering.Item Control of Magnetic Robots: Solid Medium Transmission and Milli-Scale Magnetic Swimmer(2020-12) Zhao, Haoran; Becker, Aaron T.; Han, Zhu; Faghih, Rose T.; Ruchhoeft, Paul; Pan, Miao; Leclerc, JulienMagnetic robots show great potential for revolutionizing many aspects of medicine and clinical applications. The human body is transparent to a low-frequency magnetic field. Generally, a low frequency is considered less than 300 Hz. Magnetic resonance imaging (MRI) systems typically use a maximum slew rate of 200 mT/m/ms to limit the frequency. MRI is a powerful diagnostic modality for interventions and surgeries. However, MRIs are not used for performing interventions because the MRI has a very high magnetic field and is size constrained. The MRI opening is typically a cylinder that is 30cm in diameter and must accommodate a patient, gradient coils, and the MRI bed. This dissertation provides the design and implementation of a remotely-driven, MR-compatible robotic manipulator, and a force transmission mechanism for controlling that robot. Magnetism is also a promising modality for controlling robots. Magnetically actuated robots could perform minimally invasive surgery. Such robots could be employed for many clinical and biomedical applications, ranging from in vitro to in vivo applications of diagnosis and therapy. Part two of this dissertation examines the control, design optimization, and applications of a spiral shaped magnetic robot. The primary application is focused on blood clot removal. For clot removal, magnetic robots should be controlled and navigated in 3D environments. This requires control algorithms for high accuracy path-following in 3D fluidic environments. The dissertation provides frameworks, design concepts, and control theories for accurate control during blood clot removal. A further change for clot removal is that the clots are removed deep inside the human body. These areas are not visible to cameras, so control of the robots requires imaging techniques. This dissertation presents a process using an ultrasound scanner mounted on a six-axis robot arm to image and tracking the 6 mm long by 2.5 mm diameter magnetic swimmer as it moving in models of human vasculature.Item Controlling a Swarm of Robots Using Global Inputs(2018-08) Shahrokhi, Shiva; Becker, Aaron T.; Kavraki, Lydia; Brankovic, Stanko R.; Mayerich, David; Faghih, Rose T.Microrobotics has the potential to revolutionize many applications, including targeted material delivery, assembly, and surgery. The same properties that promise breakthrough solutions---small size and large populations---present unique challenges for controlling motion. When there are more particles than control inputs, the system is underactuated and requires new control techniques. Rather than focusing on a specific microrobotic system, this dissertation designs control laws and algorithms for steering many particles controlled by global fields. First, we identify key parameters for particle manipulation by using a collection of online games where players steer swarms of up to 500 particles to complete manipulation challenges. Inspired by techniques where human operators performed well, we investigate controllers that only use the mean and variance of the swarm. We next derive automatic controllers for these and a hysteresis-based switching control to regulate the first two moments of the particle distribution. Torque control is also necessary for manipulating objects as well as for aligning sensors, emitters, or redirecting an incoming signal. Second, this dissertation proves that swarm torque control is possible, then presents algorithms to automate the task. Torque control enables us to control the position and orientation of an object. Finally, this dissertation investigates particle control with uniform magnetic gradients (the same force is applied everywhere in the workspace). We provide position control algorithms that only require non-slip wall contact in 2D. The walls of in vivo and artificial environments often have surface roughness such that the particles do not move unless actuation pulls them away from the wall. We assume that particles in contact with the boundaries have zero velocity if the shared control input pushes the particle into the wall. All the results are validated with simulations and hardware implementations.Item Controlling Many Differential- Drive Robots with Uniform Control Inputs(International Journal of Robotics Research, 8/29/2014) Becker, Aaron T.; Onyuksel, Cem; Bretl, Timothy W.; McLurkin, JamesThis paper derives both open-loop and closed-loop control policies that steer a finite set of differential-drive robots to desired positions in a two-dimensional workspace, when all robots receive the same control inputs but each robot turns at a slightly different rate. In the absence of perturbation, the open-loop policy achieves zero error in finite time. In the presence of perturbation, the closed-loop policy is globally asymptotically stabilizing with state feedback. Both policies were validated with hardware experiments using up to 15 robots. These experimental results suggest that similar policies might be applied to control micro- and nanoscale robotic systems, which are often subject to similar constraints.Item Deploying Sensor Modules with Remotely Operated Underwater Robots for Marine Data Collection(2017-10-12) Lonsford, JarrettOcean Big Data (OBD) has become prominent in environmental monitoring, offshore exploration and military surveillance. Secure transfer of this data to the surface can be challenging. Magnetic induction (MI) and visible light communications (VLC) have relatively small ranges. Our approach uses a remotely operated vehicle (ROV) swarm to deploy, recharge and retrieve sensors.Item Design and Control of a Magnetic Hammer Millirobot for Tissue Penetration(2017-05) Vichattumadom Ramakrishnan, Ashwin; Grigoriadis, Karolos M.; Becker, Aaron T.; Chen, Yi-Chao; Tsekos, Nikolaos V.Millirobots propelled by magnetic fields show promise for minimally invasive surgery or drug delivery. MRI scanners can generate magnetic gradients to apply propulsive forces on ferromagnetic objects. However, MRI gradient forces are insufficient for tissue penetration. This project presents a millirobot design and control methods to produce pulsed forces. A ferromagnetic sphere inside a hollow robot body can move back and forth between a spring and an impact rod. Repeated impacts convert the kinetic energy of the sphere into large pulsed forces that can penetrate tissue. An estimator helps achieve the maximum possible average impact velocity with minimal sensing, for a given set of material and geometric parameters, and input magnetic gradient force. Prototypes were 3D printed and tested on a custom magnetic test bed. Analytical, numerical and experimental results are presented.Item DIELECTRIC ELASTOMER TUBULAR ACTUATORS: MODELING, CONTROL, AND BIOMEDICAL APPLICATIONS(2023-12) Kaaya, Theophilus Ssebalabye; Chen, Zheng; Becker, Aaron T.; Franchek, Matthew A.; Grigoriadis, Karolos M.; Song, GangbingDielectric elastomers, a class of electro active polymers, have found applications in a vast array of fields such as soft robotics, haptic devices, biomedical devices, energy harvesting, tunable lenses, soft sensing, microfluidics, and textile electronics. This work explores the multifaceted domain of dielectric elastomers, encompassing physics-based modeling, state boundary avoidance control for safety assurance and real time control, and diverse applications including a dielectric elastomer-enabled cuff device, and a prosthetic finger. The first section delves into the intricate physics-based modeling techniques employed to simulate the behavior of dielectric elastomers under various conditions. In particular, a tubular dielectric actuator is discussed. By leveraging fundamental principles of electromechanics and material science, researchers have developed sophisticated models that enhance our understanding of the material’s response to electrical stimuli. The second focal point of this work is the implementation of state boundary avoidance control for ensuring the internal state safety of dielectric elastomer-based devices. As these materials can undergo substantial deformations in response to electric fields, preventing undesired states and ensuring controlled actuation is crucial. A state boundary avoidance control strategy is discussed as an effective mechanism to mitigate potential risks and enhance the reliability of dielectric elastomer systems. The work also highlights two innovative applications of dielectric elastomer technology. Firstly, a dielectric elastomer-enabled cuff device is presented, showcasing the material’s potential in wearable technology for therapeutic or assistive purposes. Secondly, the development of a dielectric elastomer-enabled prosthetic finger is explored, emphasizing the adaptability and precision achievable through the integration of these materials in bioengineering applications. Finally, the work provides a concise summary of the discussed topics and outlines potential future directions in dielectric elastomer research. Considerations for further advancements in modeling techniques, safety assurance protocols, and novel applications are addressed. The integration of dielectric elastomers into diverse fields holds promise for transformative technological advancements, with ongoing research poised to unlock new possibilities and refine existing applications.Item Drone Measurements of Wetland Soils & Robotic Manipulation of Ensembles Using Global Forces(2021-05) Montano Baez, Victor; Grigoriadis, Karolos M.; Jafari, Navid H.; Becker, Aaron T.; Franchek, Matthew A.This thesis covers two applications of robotics. The first section explores the use of drones for measuring properties of soil. Technologies in this section were developed to aid coastal scientists and geotechnical engineers in the structural analysis of wetland environ- ments. These include ballistic sensors inspired by free-fall penetrometers that were designed to be deployed and retrieved by drones. They exploit the deceleration experienced upon impacting moist soils to infer on soil resistance. In later developments, these sensors are made to also retrieve soil samples while simultaneously performing soil strength tests. Ex- periments are performed in simulated environments to demonstrate the use of the developed sensors for collecting soil strength parameters, retrieving soil samples, and also to study the effort required for drone retrieval within the context of pull forces. Overcoming some of the challenges associated with retrieval are discussed, and some solutions are presented. The second section examines using global forces to move large numbers of particles at the same time into desired goal positions. This process for manipulation uses the properties of boundary walls to shape the ensemble, including the shape of the walls and friction between the boundary and the particles. Experiments that verify theories on this style of manipulation are presented, along with tools that simplify hardware experiments of this variety.