Matching Items (5)
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- Creators: Computer Science and Engineering Program
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Description
Many industries require workers in warehouse and stockroom environments to perform frequent lifting tasks. Over time these repeated tasks can lead to excess strain on the worker's body and reduced productivity. This project seeks to develop an exoskeletal wrist fixture to be used in conjunction with a powered exoskeleton arm to aid workers performing box lifting types of tasks. Existing products aimed at improving worker comfort and productivity typically employ either fully powered exoskeleton suits or utilize minimally powered spring arms and/or fixtures. These designs either reduce stress to the user's body through powered arms and grippers operated via handheld controls which have limited functionality, or they use a more minimal setup that reduces some load, but exposes the user's hands and wrists to injury by directing support to the forearm. The design proposed here seeks to strike a balance between size, weight, and power requirements and also proposes a novel wrist exoskeleton design which minimizes stress on the user's wrists by directly interfacing with the object to be picked up. The design of the wrist exoskeleton was approached through initially selecting degrees of freedom and a ROM (range of motion) to accommodate. Feel and functionality were improved through an iterative prototyping process which yielded two primary designs. A novel "clip-in" method was proposed to allow the user to easily attach and detach from the exoskeleton. Designs utilized a contact surface intended to be used with dry fibrillary adhesives to maximize exoskeleton grip. Two final designs, which used two pivots in opposite kinematic order, were constructed and tested to determine the best kinematic layout. The best design had two prototypes created to be worn with passive test arms that attached to the user though a specially designed belt.
ContributorsGreason, Kenneth Berend (Author) / Sugar, Thomas (Thesis director) / Holgate, Matthew (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
In order for assistive mobile robots to operate in the same environment as humans, they must be able to navigate the same obstacles as humans do. Many elements are required to do this: a powerful controller which can understand the obstacle, and power-dense actuators which will be able to achieve the necessary limb accelerations and output energies. Rapid growth in information technology has made complex controllers, and the devices which run them considerably light and cheap. The energy density of batteries, motors, and engines has not grown nearly as fast. This is problematic because biological systems are more agile, and more efficient than robotic systems. This dissertation introduces design methods which may be used optimize a multiactuator robotic limb's natural dynamics in an effort to reduce energy waste. These energy savings decrease the robot's cost of transport, and the weight of the required fuel storage system. To achieve this, an optimal design method, which allows the specialization of robot geometry, is introduced. In addition to optimal geometry design, a gearing optimization is presented which selects a gear ratio which minimizes the electrical power at the motor while considering the constraints of the motor. Furthermore, an efficient algorithm for the optimization of parallel stiffness elements in the robot is introduced. In addition to the optimal design tools introduced, the KiTy SP robotic limb structure is also presented. Which is a novel hybrid parallel-serial actuation method. This novel leg structure has many desirable attributes such as: three dimensional end-effector positioning, low mobile mass, compact form-factor, and a large workspace. We also show that the KiTy SP structure outperforms the classical, biologically-inspired serial limb structure.
ContributorsCahill, Nathan M (Author) / Sugar, Thomas (Thesis advisor) / Ren, Yi (Thesis advisor) / Holgate, Matthew (Committee member) / Berman, Spring (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2017
Description
NGExtract 2 is a complete transistor (MOSFET) parameter extraction solution based upon the original computer program NGExtract by Rahul Shringarpure written in February 2007. NGExtract 2 is written in Java and based around the circuit simulator NGSpice. The goal of the program is to be used to produce accurate transistor models based around real-world transistor data. The program contains numerous improvements to the original program:
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
ContributorsVetrano, Michael Thomas (Author) / Allee, David (Thesis director) / Gorur, Ravi (Committee member) / Bakkaloglu, Bertan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Customers in the modern world are accustomed to having immediate and simple access to an immense amount of information, and demand this immediacy in all businesses, especially in the restaurant industry. Now more than ever, restaurants are relying on third party delivery services such as UberEATS, Postmates, and GrubHub to satiate the appetite of their delivery market, and while this may seem like the natural progression, not all restaurant owners are comfortable moving in this direction. Pain points range from not wanting a third party to represent their business or the lack of supervision over the food in transit, and the time it takes to navigate the delivery landscape, to the fact that some food just doesn’t “travel” well. In addition to this, food delivery services can cause increased stress on a kitchen, and dig into the bottom line of an already slim restaurant margin. Simply put, customer reliance on these applications puts apprehensive restaurant owners at a competitive disadvantage.Our solution is simple—we want business owners to be able to take advantage of the huge market provided by third party delivery services, without the fear of compromising their brand. At DLVR Consulting, we listen to specific pain points of a customer and alleviate them through solutions developed by our in-house food, restaurant, and branding experts. Whether creating an entirely new “delivery” brand, menu curation, or payment processing service, we give the customer exactly what they need to feel comfortable using third-party delivery applications. In this plan, we will first take a deep dive into the problem and opportunity identified by both third-party research and first-hand interviews with successful restaurant owners and operators. After exploring the problem, we will propose our solution, who we will target with said solution, and what makes this solution unique and sellable. From here we will begin to explore the execution of our ideas, including our sales and marketing plans which will work in conjunction with our go-to-market strategy. We will explore key milestones and metrics we hope to meet in the coming year, as well as the team which will be taking DLVR from a plan to an implemented business. We will take a look at our three year financial forecast, and break this down further to monthly revenue, direct costs, and expenses. We will finish by taking a look at our required funding, and how we will attempt to gain said funding.
ContributorsClancy, Kevin (Co-author, Co-author) / Sebold, Brent (Thesis director) / Clancy, Keith (Committee member) / Computer Science and Engineering Program (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Low-level optimization is the process of handwriting key parts of applications in assembly code that is better than what can be generated from a higher-level language. In performance-intensive applications, this is key to ensuring efficient code. This is generally something that is taught in on the job training, but knowledge of it improves college student’s skill sets and makes them more desirable employees
I have created material for a course teaching this low-level optimization with assembly code. I specifically focus on the x86 architecture, as this is one of the most prolific computer architectures. The course contains a series of lecture videos, live coding videos, and structured programming assignments to support the learning objectives. This material is presented in an entirely autonomous way, which serves as remote learning material and can be easily added as supplemental material to an existing course.
ContributorsAbraham, Jacob (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05