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Description
With the advent of GPGPU, many applications are being accelerated by using CUDA programing paradigm. We are able to achieve around 10x -100x speedups by simply porting the application on to the GPU and running the parallel chunk of code on its multi cored SIMT (Single instruction multiple thread) architecture. But for optimal performance it is necessary to make sure that all the GPU resources are efficiently used, and the latencies in the application are minimized. For this, it is essential to monitor the Hardware usage of the algorithm and thus diagnose the compute and memory bottlenecks in the implementation. In the following thesis, we will be analyzing the mapping of CUDA implementation of BLIINDS-II algorithm on the underlying GPU hardware, and come up with a Kepler architecture specific solution of using shuffle instruction via CUB library to tackle the two major bottlenecks in the algorithm. Experiments were conducted to convey the advantage of using shuffle instru3ction in algorithm over only using shared memory as a buffer to global memory. With the new implementation of BLIINDS-II algorithm using CUB library, a speedup of around 13.7% was achieved.
ContributorsWadekar, Ameya (Author) / Sohoni, Sohum (Thesis advisor) / Aukes, Daniel (Committee member) / Redkar, Sangram (Committee member) / Arizona State University (Publisher)
Created2017
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
This thesis presents the design and testing of a soft robotic device for water utility pipeline inspection. The preliminary findings of this new approach to conventional methods of pipe inspection demonstrate that a soft inflatable robot can successfully traverse the interior space of a range of diameter pipes using pneumatic and without the need to adjust rigid, mechanical components. The robot utilizes inflatable soft actuators with an adjustable radius which, when pressurized, can provide a radial force, effectively anchoring the device in place. Additional soft inflatable actuators translate forces along the center axis of the device which creates forward locomotion when used in conjunction with the radial actuation. Furthermore, a bio-inspired control algorithm for locomotion allows the robot to maneuver through a pipe by mimicking the peristaltic gait of an inchworm. This thesis provides an examination and evaluation of the structure and behavior of the inflatable actuators through computational modeling of the material and design, as well as the experimental data of the forces and displacements generated by the actuators. The theoretical results are contrasted with/against experimental data utilizing a physical prototype of the soft robot. The design is anticipated to enable compliant robots to conform to the space offered to them and overcome occlusions from accumulated solids found in pipes. The intent of the device is to be used for inspecting existing pipelines owned and operated by Salt River Project, a Phoenix-area water and electricity utility provider.
ContributorsAdams, Wade Silas (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
This thesis aims to design of wings for a laminate biped robot for providing locomotion stabilization during jump gliding. The wings are designed to collapse down during the jumping phase to maximize jump height and deployed back for gliding phase using anisotropic buckling in tape spring hinges. The project aims to develop a reliable dynamics model which can be utilized for design and evaluation of optimized systems for jump-gliding. The aerodynamic simulations are run on a vortex-lattice code which provides numeric simulations of the defined geometric bodies. The aerodynamic simulations assist in improving the design parameters such as planform, camber and twist to achieve the best possible Coefficient of Lift for maximizing glide distance. The aerodynamic simulation output is then plugged into a dynamics model built in Python, which is validated and correlated with experimental testing of a key wing designs. The experimental results are then utilized to improve the dynamics model and obtain better designs for improved performance. The simulation model informs the aerodynamic design of wings for sustaining glide for the biped platform and maximizing glide length to increase range.
ContributorsGadekar, Vipul (Author) / Takahashi, Timothy (Thesis advisor) / Aukes, Daniel (Thesis advisor) / Marvi, Hamidreza (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