Browsing by Subject "Automation"

Now showing 1 - 7 of 7
  • Thumbnail Image
    Item
    An Automated Grid-Based Robotic Alignment System for Pick and Place Applications
    (2013-12) Bearden, Lukas R.; Razban, Ali; Wasfy, Tamer; Li, Lingxi; Anwar, Sohel
    This thesis proposes an automated grid-based alignment system utilizing lasers and an array of light-detecting photodiodes. The intent is to create an inexpensive and scalable alignment system for pick-and-place robotic systems. The system utilizes the transformation matrix, geometry, and trigonometry to determine the movements to align the robot with a grid-based array of photodiodes. The alignment system consists of a sending unit utilizing lasers, a receiving module consisting of photodiodes, a data acquisition unit, a computer-based control system, and the robot being aligned. The control system computes the robot movements needed to position the lasers based on the laser positions detected by the photodiodes. A transformation matrix converts movements from the coordinate system of the grid formed by the photodiodes to the coordinate system of the robot. The photodiode grid can detect a single laser spot and move it to any part of the grid, or it can detect up to four laser spots and use their relative positions to determine rotational misalignment of the robot. Testing the alignment consists of detecting the position of a single laser at individual points in a distinct pattern on the grid array of photodiodes, and running the entire alignment process multiple times starting with different misalignment cases. The first test provides a measure of the position detection accuracy of the system, while the second test demonstrates the alignment accuracy and repeatability of the system. The system detects the position of a single laser or multiple lasers by using a method similar to a center-of-gravity calculation. The intensity of each photodiode is multiplied by the X-position of that photodiode. The summed result from each photodiode intensity and position product is divided by the summed value of all of the photodiode intensities to get the X-position of the laser. The same thing is done with the Y-values to get the Y-position of the laser. Results show that with this method the system can read a single laser position value with a resolution of 0.1mm, and with a maximum X-error of 2.9mm and Y-error of 2.0mm. It takes approximately 1.5 seconds to process the reading. The alignment procedure calculates the initial misalignment between the robot and the grid of photodiodes by moving the robot to two distinct points along the robot’s X-axis so that only one laser is over the grid. Using these two detected points, a movement trajectory is generated to move that laser to the X = 0, Y = 0 position on the grid. In the process, this moves the other three lasers over the grid, allowing the system to detect the positions of four lasers and uses the positions to determine the rotational and translational offset needed to align the lasers to the grid of photodiodes. This step is run in a feedback loop to update the adjustment until it is within a permissible error value. The desired result for the complete alignment is a robot manipulator positioning within ±0.5mm along the X and Y-axes. The system shows a maximum error of 0.2mm in the X-direction and 0.5mm in the Y-direction with a run-time of approximately 4 to 5 minutes per alignment. If the permissible error value of the final alignment is tripled the alignment time goes down to 1 to 1.5 minutes and the maximum error goes up to 1.4mm in both the X and Y-directions. The run time of the alignment decreases because the system runs fewer alignment iterations.
  • Thumbnail Image
    Item
    The Automated Home Window Project
    (2020-04-30) Ashcraft, Samuel; Bessesen, Chad; Burke, Alyssa; Weissbach, Robert
    Terry Walden, a homebuilder and the project sponsor, expressed the need for a vinyl window that can be controlled electronically by a cell phone application. The window will be automated using a Wi-Fi Stepper Microcontroller, a NEMA 23 stepper motor, a worm-gear, and an android application. The automated window will operate by pressing a button on the android phone. This button will send a script to the microcontroller board. From there, the board will control the stepper motor that is attached to the worm gear, effectively closing or opening the window depending on which button was pressed. The frame of the window and the window itself are provided by the sponsor. In order to meet sponsor requirements, the entire electrical and mechanical pieces will fit within a 4inch envelope above the window. The window will fully open, or fully close, within 10 seconds and the voltage to each window will not exceed ~24 VDC. There is an overcurrent sensor that will determine when the window is fully open, fully closed, or obstructed by a foreign object for safety. Opening the window will still be possible manually. The system will operate within the sponsor's needs as it meets each requirement listed in the Specifications Requirements table - which can be found in Chapter 2. To verify that the automated window has met the functional specifications, the test procedures were implemented. The testing specifications have been approved by both the sponsor and Dr. Weissbach. The results of the tests can be found in the Test Specifications document of the report and more information can be found in Chapter 5 of this report.
  • Thumbnail Image
    Item
    Automated pancreatic cyst screening using natural language processing: a new tool in the early detection of pancreatic cancer
    (Elsevier, 2015-05) Roch, Alexandra M.; Mehrabi, Saeed; Krishnan, Anand; Schmidt, Heidi E.; Kesterson, Joseph; Beesley, Chris; Dexter, Paul R.; Palakal, Matthew; Schmidt, C. Max; Department of Surgery, IU School of Medicine
    INTRODUCTION: As many as 3% of computed tomography (CT) scans detect pancreatic cysts. Because pancreatic cysts are incidental, ubiquitous and poorly understood, follow-up is often not performed. Pancreatic cysts may have a significant malignant potential and their identification represents a 'window of opportunity' for the early detection of pancreatic cancer. The purpose of this study was to implement an automated Natural Language Processing (NLP)-based pancreatic cyst identification system. METHOD: A multidisciplinary team was assembled. NLP-based identification algorithms were developed based on key words commonly used by physicians to describe pancreatic cysts and programmed for automated search of electronic medical records. A pilot study was conducted prospectively in a single institution. RESULTS: From March to September 2013, 566,233 reports belonging to 50,669 patients were analysed. The mean number of patients reported with a pancreatic cyst was 88/month (range 78-98). The mean sensitivity and specificity were 99.9% and 98.8%, respectively. CONCLUSION: NLP is an effective tool to automatically identify patients with pancreatic cysts based on electronic medical records (EMR). This highly accurate system can help capture patients 'at-risk' of pancreatic cancer in a registry.
  • Thumbnail Image
    Item
    Automated Ramen Noodle Vending Machine
    (2018-12-04) Ragozzino, Dan R.; Goodman, David
    Contained in the following report is a complete and detailed document of the design and implementation for the development of an automated ramen noodle vending machine unit. Covered topics include justification and specification development, which considers target consumer audience as well as some considerations for safety ratings and features that are required for consumer appliances. Also covered is the development and implementation phase, entailing translating design into a physical and functional prototype that achieves specifications detailed in the design phase. There are three major components of the development phase: hardware, interface and software. Each component of development is covered in detail, including troubleshooting and on-the-fly changes made to design to accommodate issues that arise during the prototype development. The last section of the document includes some considerations for iterative design. Issues encountered during prototype development will also be documented. A fully detailed operations guide will also be included. In the appendices of the document are the full printout of the software, detailed spec sheets of individual hardware components, as well as documents from the design phase.
  • Thumbnail Image
    Item
    Distributed Monocular SLAM for Indoor Map Building
    (Hindawi, 2017) Egodagamage, Ruwan; Tuceryan, Mihran; Computer and Information Science, School of Science
    Utilization and generation of indoor maps are critical elements in accurate indoor tracking. Simultaneous Localization and Mapping (SLAM) is one of the main techniques for such map generation. In SLAM an agent generates a map of an unknown environment while estimating its location in it. Ubiquitous cameras lead to monocular visual SLAM, where a camera is the only sensing device for the SLAM process. In modern applications, multiple mobile agents may be involved in the generation of such maps, thus requiring a distributed computational framework. Each agent can generate its own local map, which can then be combined into a map covering a larger area. By doing so, they can cover a given environment faster than a single agent. Furthermore, they can interact with each other in the same environment, making this framework more practical, especially for collaborative applications such as augmented reality. One of the main challenges of distributed SLAM is identifying overlapping maps, especially when relative starting positions of agents are unknown. In this paper, we are proposing a system having multiple monocular agents, with unknown relative starting positions, which generates a semidense global map of the environment.
  • Thumbnail Image
    Item
    The McKinsey Study and the Future of Library Work
    (2017-11) Lewis, David W.
    Reviews the prospects for the library workforce in light of the McKinsey Global Institute study, A Future That Works: Automation, Employment, and Productivity, on automation and its effect on various jobs and job activities. The McKinsey report projects that library jobs can be automated to a large extent. The paper argues that while the McKinsey report may over estimate the extent that library jobs can be automated, this should be a concern to librarians and libraries.
  • Thumbnail Image
    Item
    Toward Automation of the Supine Pressor Test for Preeclampsia
    (American Society of Mechanical Enginners, 2019-11) Qureshi, Hamna J.; Ma, Jessica L.; Anderson, Jennifer L.; Bosinski, Brett M.; Acharya, Aditi; Bennett, Rachel D.; Haas, David M.; Cox, Abigail D.; Wodicka, George R.; Reuter, David G.; Goergen, Craig J.; Medicine, School of Medicine
    Preeclampsia leads to increased risk of morbidity and mortality for both mother and fetus. Most previous studies have largely neglected mechanical compression of the left renal vein by the gravid uterus as a potential mechanism. In this study, we first used a murine model to investigate the pathophysiology of left renal vein constriction. The results indicate that prolonged renal vein stenosis after 14 days can cause renal necrosis and an increase in blood pressure (BP) of roughly 30 mmHg. The second part of this study aimed to automate a diagnostic tool, known as the supine pressor test (SPT), to enable pregnant women to assess their preeclampsia development risk. A positive SPT has been previously defined as an increase of at least 20 mmHg in diastolic BP when switching between left lateral recumbent and supine positions. The results from this study established a baseline BP increase between the two body positions in nonpregnant women and demonstrated the feasibility of an autonomous SPT in pregnant women. Our results demonstrate that there is a baseline increase in BP of roughly 10-14 mmHg and that pregnant women can autonomously perform the SPT. Overall, this work in both rodents and humans suggests that (1) stenosis of the left renal vein in mice leads to elevation in BP and acute renal failure, (2) nonpregnant women experience a baseline increase in BP when they shift from left lateral recumbent to supine position, and (3) the SPT can be automated and used autonomously.