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Description
As robots are increasingly migrating out of factories and research laboratories and into our everyday lives, they should move and act in environments designed for humans. For this reason, the need of anthropomorphic movements is of utmost importance. The objective of this thesis is to solve the inverse kinematics problem

As robots are increasingly migrating out of factories and research laboratories and into our everyday lives, they should move and act in environments designed for humans. For this reason, the need of anthropomorphic movements is of utmost importance. The objective of this thesis is to solve the inverse kinematics problem of redundant robot arms that results to anthropomorphic configurations. The swivel angle of the elbow was used as a human arm motion parameter for the robot arm to mimic. The swivel angle is defined as the rotation angle of the plane defined by the upper and lower arm around a virtual axis that connects the shoulder and wrist joints. Using kinematic data recorded from human subjects during every-day life tasks, the linear sensorimotor transformation model was validated and used to estimate the swivel angle, given the desired end-effector position. Defining the desired swivel angle simplifies the kinematic redundancy of the robot arm. The proposed method was tested with an anthropomorphic redundant robot arm and the computed motion profiles were compared to the ones of the human subjects. This thesis shows that the method computes anthropomorphic configurations for the robot arm, even if the robot arm has different link lengths than the human arm and starts its motion at random configurations.
ContributorsWang, Yuting (Author) / Artemiadis, Panagiotis (Thesis advisor) / Mignolet, Marc (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Electromyogram (EMG)-based control interfaces are increasingly used in robot teleoperation, prosthetic devices control and also in controlling robotic exoskeletons. Over the last two decades researchers have come up with a plethora of decoding functions to map myoelectric signals to robot motions. However, this requires a lot of training and validation

Electromyogram (EMG)-based control interfaces are increasingly used in robot teleoperation, prosthetic devices control and also in controlling robotic exoskeletons. Over the last two decades researchers have come up with a plethora of decoding functions to map myoelectric signals to robot motions. However, this requires a lot of training and validation data sets, while the parameters of the decoding function are specific for each subject. In this thesis we propose a new methodology that doesn't require training and is not user-specific. The main idea is to supplement the decoding functional error with the human ability to learn inverse model of an arbitrary mapping function. We have shown that the subjects gradually learned the control strategy and their learning rates improved. We also worked on identifying an optimized control scheme that would be even more effective and easy to learn for the subjects. Optimization was done by taking into account that muscles act in synergies while performing a motion task. The low-dimensional representation of the neural activity was used to control a two-dimensional task. Results showed that in the case of reduced dimensionality mapping, the subjects were able to learn to control the device in a slower pace, however they were able to reach and retain the same level of controllability. To summarize, we were able to build an EMG-based controller for robot devices that would work for any subject, without any training or decoding function, suggesting human-embedded controllers for robotic devices.
ContributorsAntuvan, Chris Wilson (Author) / Artemiadis, Panagiotis (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives

Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives a strong representation of these characteristics. Many previous studies have shown that the arm posture is a dominant factor for determining the end point impedance in a horizontal plane (transverse plane). The objective of this thesis is to characterize end point impedance of the human arm in the three dimensional (3D) space. Moreover, it investigates and models the control of the arm impedance due to increasing levels of muscle co-contraction. The characterization is done through experimental trials where human subjects maintained arm posture, while perturbed by a robot arm. Moreover, the subjects were asked to control the level of their arm muscles' co-contraction, using visual feedback of their muscles' activation, in order to investigate the effect of the muscle co-contraction on the arm impedance. The results of this study showed a very interesting, anisotropic increase of the arm stiffness due to muscle co-contraction. This can lead to very useful conclusions about the arm biomechanics as well as many implications for human motor control and more specifically the control of arm impedance through muscle co-contraction. The study finds implications for the EMG-based control of robots that physically interact with humans.
ContributorsPatel, Harshil Naresh (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Energy efficient design and management of data centers has seen considerable interest in the recent years owing to its potential to reduce the overall energy consumption and thereby the costs associated with it. Therefore, it is of utmost importance that new methods for improved physical design of data centers, resource

Energy efficient design and management of data centers has seen considerable interest in the recent years owing to its potential to reduce the overall energy consumption and thereby the costs associated with it. Therefore, it is of utmost importance that new methods for improved physical design of data centers, resource management schemes for efficient workload distribution and sustainable operation for improving the energy efficiency, be developed and tested before implementation on an actual data center. The BlueTool project, provides such a state-of-the-art platform, both software and hardware, to design and analyze energy efficiency of data centers. The software platform, namely GDCSim uses cyber-physical approach to study the physical behavior of the data center in response to the management decisions by taking into account the heat recirculation patterns in the data center room. Such an approach yields best possible energy savings owing to the characterization of cyber-physical interactions and the ability of the resource management to take decisions based on physical behavior of data centers. The GDCSim mainly uses two Computational Fluid Dynamics (CFD) based cyber-physical models namely, Heat Recirculation Matrix (HRM) and Transient Heat Distribution Model (THDM) for thermal predictions based on different management schemes. They are generated using a model generator namely BlueSim. To ensure the accuracy of the thermal predictions using the GDCSim, the models, HRM and THDM and the model generator, BlueSim need to be validated experimentally. For this purpose, the hardware platform of the BlueTool project, namely the BlueCenter, a mini data center, can be used. As a part of this thesis, the HRM and THDM were generated using the BlueSim and experimentally validated using the BlueCenter. An average error of 4.08% was observed for BlueSim, 5.84% for HRM and 4.24% for THDM. Further, a high initial error was observed for transient thermal prediction, which is due to the inability of BlueSim to account for the heat retained by server components.
ContributorsGilbert, Rose Robin (Author) / Gupta, Sandeep K.S (Thesis advisor) / Artemiadis, Panagiotis (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2012
Description
The study of the mechanical behavior of nanocrystalline metals using microelectromechanical systems (MEMS) devices lies at the intersection of nanotechnology, mechanical engineering and material science. The extremely small grains that make up nanocrystalline metals lead to higher strength but lower ductility as compared to bulk metals. Effects of strain-rate dependence

The study of the mechanical behavior of nanocrystalline metals using microelectromechanical systems (MEMS) devices lies at the intersection of nanotechnology, mechanical engineering and material science. The extremely small grains that make up nanocrystalline metals lead to higher strength but lower ductility as compared to bulk metals. Effects of strain-rate dependence on the mechanical behavior of nanocrystalline metals are explored. Knowing the strain rate dependence of mechanical properties would enable optimization of material selection for different applications and lead to lighter structural components and enhanced sustainability.
ContributorsHall, Andrea Paulette (Author) / Rajagopalan, Jagannathan (Thesis director) / Liao, Yabin (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
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Description
This paper investigates Surface Mechanical Attrition Treatment (SMAT) and the influence of treatment temperature and initial sample surface finish on the corrosion resistance of 7075-T651 aluminum alloy. Ambient SMAT was performed on AA7075 samples polished to 80-grit initial surface roughness. Potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) tests were used

This paper investigates Surface Mechanical Attrition Treatment (SMAT) and the influence of treatment temperature and initial sample surface finish on the corrosion resistance of 7075-T651 aluminum alloy. Ambient SMAT was performed on AA7075 samples polished to 80-grit initial surface roughness. Potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) tests were used to characterize the corrosion behavior of samples before and after SMAT. Electrochemical tests indicated an improved corrosion resistance after application of SMAT process. The observed improvements in corrosion properties are potentially due to microstructural changes in the material surface induced by SMAT which encouraged the formation of a passive oxide layer. Further testing and research are required to understand the corrosion related effects of cryogenic SMAT and initial-surface finish as the COVID-19 pandemic inhibited experimentation plans.
ContributorsDeorio, Jordan Anthony (Author) / Solanki, Kiran (Thesis director) / Rajagopalan, Jagannathan (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
An approach for modeling resistance spot welding of thin-gauge, dissimilar metal sheets with high electrical conductivity is presented in this work. In this scenario, the electrical and thermal contact resistances play a dominant role in heat generation and temperature evolution within the workpieces; these interactions ultimately control the weld geometry.

An approach for modeling resistance spot welding of thin-gauge, dissimilar metal sheets with high electrical conductivity is presented in this work. In this scenario, the electrical and thermal contact resistances play a dominant role in heat generation and temperature evolution within the workpieces; these interactions ultimately control the weld geometry. Existing models are limited in modeling these interactions, especially for dissimilar and thin-gauge metal sheets, and at higher temperatures when the multiphysics becomes increasingly interdependent. The approach presented here uses resistivity measurements, combined with thermal modeling and known bulk resistance relationships to infer the relationship between electrical contact resistance and temperature for each of the different material interfaces in the welding process. Corresponding thermal contact resistance models are developed using the Wiedemann-Franz law combined with a scaling factor to account for nonmetallic behavior. Experimental and simulation voltage histories and final weld diameter were used to validate this model for a Cu/Al/Cu and a Cu/Al/Cu/Al/Cu stack-ups. This model was then used to study the effect of Ni-P coating on resistance spot welding of Cu and Al sheets in terms of weld formation, mechanical deformation, and contact resistance. Contact resistance and current density distribution are highly dependent on contact pressure and temperature distribution at the Cu/Al interface in the presence of alumina. The Ni-P coating helps evolve a partially-bonded donut shaped weld into a fully-bonded hourglass-shaped weld by decreasing the dependence of contact resistance and current density distribution on contact pressure and temperature distribution at the Cu/Al interface. This work also provides an approach to minimize distortion due to offset-rolling in thin aluminum sheets by optimizing the stiffening feature geometry. The distortion is minimized using particle swarm optimization. The objective function is a function of distortion and smallest radius of curvature in the geometry. Doubling the minimum allowable radius of curvature nearly doubles the reduction in distortion from the stadium shape for a quarter model. Reduction in distortion in the quarter model extends to the full-scale model with the best design performing 5.3% and 27% better than the corresponding nominal design for a quarter and full-scale model, respectively.
ContributorsVeeresh, Pawan (Author) / Oswald, Jay (Thesis advisor) / Carlson, Blair (Committee member) / Hoover, Christian (Committee member) / Rajagopalan, Jagannathan (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Achieving a viable process for advanced manufacturing of ceramics and metal-ceramic composites is a sought-after goal in a wide range of fields including electronics and sensors for harsh environments, microelectromechanical devices, energy storage materials, and structural materials, among others. In this dissertation, the processing, and manufacturing of ceramics and ceramic

Achieving a viable process for advanced manufacturing of ceramics and metal-ceramic composites is a sought-after goal in a wide range of fields including electronics and sensors for harsh environments, microelectromechanical devices, energy storage materials, and structural materials, among others. In this dissertation, the processing, and manufacturing of ceramics and ceramic composites are addressed, specifically, a process for three-dimensional (3D) printing of polymer-derived ceramics (PDC), and a process for low-cost manufacturing as well as healing of metal-ceramic composites is demonstrated.Three-dimensional printing of ceramics is enabled by dispensing the preceramic polymer at the tip of a moving nozzle into a gel that can reversibly switch between fluid and solid states, and subsequently thermally cross-linking the entire printed part “at once” while still inside the same gel was demonstrated. The solid gel converts to fluid at the tip of the moving nozzle, allowing the polymer solution to be dispensed and quickly returns to a solid state to maintain the geometry of the printed polymer both during printing and the subsequent high-temperature (160 °C) cross-linking. After retrieving the cross-linked part from the gel, the green body is converted to ceramic by high-temperature pyrolysis. This scalable process opens new opportunities for low-cost and high-speed production of complex three-dimensional ceramic parts and will be widely used for high-temperature and corrosive environment applications, including electronics and sensors, microelectromechanical systems, energy, and structural applications. Metal-ceramic composites are technologically significant as structural and functional materials and are among the most expensive materials to manufacture and repair. Hence, technologies for self-healing metal-ceramic composites are important. Here, a concept to fabricate and heal co-continuous metal-ceramic composites at room temperature were demonstrated. The composites were fabricated by infiltration of metal (here Copper) into a porous alumina preform (fabricated by freeze-casting) through electroplating; a low-temperature and low-cost process for the fabrication of such composites. Additionally, the same electroplating process was demonstrated for healing damages such as grooves and cracks in the original composite, such that the healed composite recovered its strength by more than 80%. Such technology may be expanded toward fully autonomous self-healing structures.
ContributorsMahmoudi, Mohammadreza (Author) / Minary-Jolandan, Majid (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Cramer, Corson (Committee member) / Kang, Wonmo (Committee member) / Bhate, Dhruv (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Magnetic liquids called ferrofluids have been used in applications ranging from audio speaker cooling and rotary pressure seals to retinal detachment surgery and implantable artificial glaucoma valves. Recently, ferrofluids have been investigated as a material for use in magnetically controllable liquid droplet robotics. Liquid droplet robotics is an emerging technology

Magnetic liquids called ferrofluids have been used in applications ranging from audio speaker cooling and rotary pressure seals to retinal detachment surgery and implantable artificial glaucoma valves. Recently, ferrofluids have been investigated as a material for use in magnetically controllable liquid droplet robotics. Liquid droplet robotics is an emerging technology that aims to apply control theory to manipulate fluid droplets as robotic agents to perform a wide range of tasks. Furthermore, magnetically controlled micro-robotics is another popular area of study where manipulating a magnetic field allows for the control of magnetized micro-robots. Both of these emerging fields have potential for impact toward medical applications: liquid characteristics such as being able to dissolve various compounds, be injected via a needle, and the potential for the human body to automatically filter and remove a liquid droplet robot, make liquid droplet robots advantageous for medical applications; while the ability to remotely control the torques and forces on an untethered microrobot via modulating the magnetic field and gradient is also highly advantageous. The research described in this dissertation explores applications and methods for the electromagnetic control of ferrofluid droplet robots. First, basic electrical components built from fluidic channels containing ferrofluid are made remotely tunable via the placement of ferrofluid within the channel. Second, a ferrofluid droplet is shown to be fully controllable in position, stretch direction, and stretch length in two dimensions using proportional-integral-derivative (PID) controllers. Third, control of a ferrofluid’s position, stretch direction, and stretch length is extended to three dimensions, and control gains are optimized via a Bayesian optimization process to achieve higher accuracy. Finally, magnetic control of both single and multiple ferrofluid droplets in two dimensions is investigated via a visual model predictive control approach based on machine learning. These achievements take both liquid droplet robotics and magnetic micro-robotics fields several steps closer toward real-world medical applications such as embedded soft electronic health monitors, liquid-droplet-robot-based drug delivery, and automated magnetically actuated surgeries.
ContributorsAhmed, Reza James (Author) / Marvi, Hamidreza (Thesis advisor) / Espanol, Malena (Committee member) / Rajagopalan, Jagannathan (Committee member) / Zhuang, Houlong (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2022
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Description
The increasing demand for structural materials with superior mechanical properties has provided a strong impetus to the discovery of novel materials, and innovations in processing techniques to improve the properties of existing materials. Methods like severe plastic deformation (SPD) and surface mechanical attrition treatment (SMAT) have led to significant enhancement

The increasing demand for structural materials with superior mechanical properties has provided a strong impetus to the discovery of novel materials, and innovations in processing techniques to improve the properties of existing materials. Methods like severe plastic deformation (SPD) and surface mechanical attrition treatment (SMAT) have led to significant enhancement in the strength of traditional structural materials like Al and Fe based alloys via microstructural refinement. However, the nanocrystalline materials produced using these techniques exhibit poor ductility due to the lack of effective strain hardening mechanisms, and as a result the well-known strength-ductility trade-off persists. To overcome this trade-off, researchers have proposed the concept of heterostructured materials, which are composed of domains ranging in size from a few nanometers to several micrometers. Over the last two decades, there has been intense research on the development of new methods to synthesize heterostructured materials. However, none of these methods is capable of providing precise control over key microstructural parameters such as average grain size, grain morphology, and volume fraction and connectivity of coarse and fine grains. Due to the lack of microstructural control, the relationship between these parameters and the deformation behavior of heterostructured materials cannot be investigated systematically, and hence designing heterostructured materials with optimized properties is currently infeasible. This work aims to address this scientific and technological challenge and is composed of two distinct but interrelated parts. The first part concerns the development of a broadly applicable synthesis method to produce heterostructured metallic films with precisely defined architectures. This method exploits two forms of film growth (epitaxial and Volmer-Weber) to generate heterostructured metallic films. The second part investigates the effect of different microstructural parameters on the deformation behavior of heterostructured metallic films with the aim of elucidating their structure-property relationships. Towards this end, freestanding heterostructured Fe films with different architectures were fabricated and uniaxially deformed using MEMS stages. The results from these experiments are presented and their implications for the mechanical properties of heterostructured materials is discussed.
ContributorsBerlia, Rohit (Author) / Rajagopalan, Jagannathan (Thesis advisor) / Sieradzki, Karl (Committee member) / Peralta, Pedro (Committee member) / Crozier, Peter (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2021