Matching Items (20)
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- All Subjects: robotics
- Creators: Computer Science and Engineering Program
Description
Many researchers aspire to create robotics systems that assist humans in common office tasks, especially by taking over delivery and messaging tasks. For meaningful interactions to take place, a mobile robot must be able to identify the humans it interacts with and communicate successfully with them. It must also be able to successfully navigate the office environment. While mobile robots are well suited for navigating and interacting with elements inside a deterministic office environment, attempting to interact with human beings in an office environment remains a challenge due to the limits on the amount of cost-efficient compute power onboard the robot. In this work, I propose the use of remote cloud services to offload intensive interaction tasks. I detail the interactions required in an office environment and discuss the challenges faced when implementing a human-robot interaction platform in a stochastic office environment. I also experiment with cloud services for facial recognition, speech recognition, and environment navigation and discuss my results. As part of my thesis, I have implemented a human-robot interaction system utilizing cloud APIs into a mobile robot, enabling it to navigate the office environment, identify humans within the environment, and communicate with these humans.
ContributorsDSouza, Daniel Anand (Author) / Kambhampati, Subbarao (Thesis director) / Zhang, Yu (Committee member) / Computer Science and Engineering Program (Contributor) / School of Computing, Informatics, and Decision Systems Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Preventive maintenance is a practice that has become popular in recent years, largely due to the increased dependency on electronics and other mechanical systems in modern technologies. The main idea of preventive maintenance is to take care of maintenance-type issues before they fully appear or cause disruption of processes and daily operations. One of the most important parts is being able to predict and foreshadow failures in the system, in order to make sure that those are fixed before they turn into large issues. One specific area where preventive maintenance is a very big part of daily activity is the automotive industry. Automobile owners are encouraged to take their cars in for maintenance on a routine schedule (based on mileage or time), or when their car signals that there is an issue (low oil levels for example). Although this level of maintenance is enough when people are in charge of cars, the rise of autonomous vehicles, specifically self-driving cars, changes that. Now instead of a human being able to look at a car and diagnose any issues, the car needs to be able to do this itself. The objective of this project was to create such a system. The Electronics Preventive Maintenance System is an internal system that is designed to meet all these criteria and more. The EPMS system is comprised of a central computer which monitors all major electronic components in an autonomous vehicle through the use of standard off-the-shelf sensors. The central computer compiles the sensor data, and is able to sort and analyze the readings. The filtered data is run through several mathematical models, each of which diagnoses issues in different parts of the vehicle. The data for each component in the vehicle is compared to pre-set operating conditions. These operating conditions are set in order to encompass all normal ranges of output. If the sensor data is outside the margins, the warning and deviation are recorded and a severity level is calculated. In addition to the individual focus, there's also a vehicle-wide model, which predicts how necessary maintenance is for the vehicle. All of these results are analyzed by a simple heuristic algorithm and a decision is made for the vehicle's health status, which is sent out to the Fleet Management System. This system allows for accurate, effortless monitoring of all parts of an autonomous vehicle as well as predictive modeling that allows the system to determine maintenance needs. With this system, human inspectors are no longer necessary for a fleet of autonomous vehicles. Instead, the Fleet Management System is able to oversee inspections, and the system operator is able to set parameters to decide when to send cars for maintenance. All the models used for the sensor and component analysis are tailored specifically to the vehicle. The models and operating margins are created using empirical data collected during normal testing operations. The system is modular and can be used in a variety of different vehicle platforms, including underwater autonomous vehicles and aerial vehicles.
ContributorsMian, Sami T. (Author) / Collofello, James (Thesis director) / Chen, Yinong (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Modern curriculum requires students to purchase expensive handheld calculators, which has created a market with little competition or incentive for improvement. The purpose of this project was to create a competitive free alternative to be used outside the classroom for those who do not have the economic stability to purchase, for example, a TI-82, which costs approximately $100. Calculat3d is an Android application that matches the general-purpose functionality of the TI-82, including calculations, basic statistical functions, graphing, and creating programs. Additionally, a programming language and interpreter were created so programs can be written inside Calculat3d and be used alongside calculations, thus expanding the functionality of the calculator. Graphing functionality is also included in Calculat3d but expanded to three dimensions as opposed to the two-dimension limited TI calculator.
ContributorsEverhart, Ryan Matthew (Author) / Hansford, Dianne (Thesis director) / Bazzi, Rida (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Technical innovation has always played a part in live theatre, whether in the form of mechanical pieces like lifts and trapdoors to the more recent integration of digital media. The advances of the art form encourage the development of technology, and at the same time, technological development enables the advancement of theatrical expression. As mechanics, lighting, sound, and visual media have made their way into the spotlight, advances in theatrical robotics continue to push for their inclusion in the director's toolbox. However, much of the technology available is gated by high prices and unintuitive interfaces, designed for large troupes and specialized engineers, making it difficult to access for small schools and students new to the medium. As a group of engineering students with a vested interest in the development of the arts, this thesis team designed a system that will enable troupes from any background to participate in the advent of affordable automation. The intended result of this thesis project was to create a robotic platform that interfaces with custom software, receiving commands and transmitting position data, and to design that software so that a user can define intuitive cues for their shows. In addition, a new pathfinding algorithm was developed to support free-roaming automation in a 2D space. The final product consisted of a relatively inexpensive (< $2000) free-roaming platform, made entirely with COTS and standard materials, and a corresponding control system with cue design, wireless path following, and position tracking. This platform was built to support 1000 lbs, and includes integrated emergency stopping. The software allows for custom cue design, speed variation, and dynamic path following. Both the blueprints and the source code for the platform and control system have been released to open-source repositories, to encourage further development in the area of affordable automation. The platform itself was donated to the ASU School of Theater.
ContributorsHollenbeck, Matthew D. (Co-author) / Wiebel, Griffin (Co-author) / Winnemann, Christopher (Thesis director) / Christensen, Stephen (Committee member) / Computer Science and Engineering Program (Contributor) / School of Film, Dance and Theatre (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This project serves as an extra learning tool for students enrolled in HEB 101 (Hebrew) at Arizona State University. This tool was developed using Axure Prototyping Software and can be used by anyone. The tool follows the HEB 101 course curriculum which also works alongside the textbook for the class (Hebrew From Scratch part 1). The tool fully covers the seven units that students learn in HEB 101. Each unit follows a standard structure. There is a unit title page which lays out the major concepts covered in the unit (i.e. personal pronouns, question words, prepositions, etc.) and links to different pages within the unit. Each unit has seven to ten lesson pages which introduce Hebrew concepts and provide exercises and examples to help the students practice the material they learned both in class and in the tool. Each unit also has links to Quizlet pages that have the units' vocab set up in a flashcard format so that they can study for upcoming quizzes and exams in the class. The Quizlet page for each unit also provides a randomly generated vocab quiz for the students. There is also a unit quiz for every unit which tests the students on the major concepts of the unit. There are also unit vocab pages that provide all the vocab covered in the unit. This tool provides students with numerous ways of practicing and mastering the material covered in the lectures. The main benefit of this tool for students is that it provides audio files for each vocabulary word learned in HEB 101 which will allow them to have quick access to the pronunciation of the words they are learning. This tool will be used in future HEB 101 classes.
ContributorsOsuna, Esteban Rene (Author) / Shemer, Judith (Thesis director) / Mirguet, Francoise (Committee member) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In order to adequately introduce students to computer science and robotics in an exciting and engaging manner certain teaching techniques should be used. In recent years some of the most popular paradigms are Visual Programming Languages. Visual Programming Languages are meant to introduce problem solving skills and basic programming constructs inherent to all modern day languages by allowing users to write programs visually as opposed to textually. By bypassing the need to learn syntax students can focus on the thinking behind developing an algorithm and see immediate results that help generate excitement for the field and reduce disinterest due to startup complexity and burnout. The Introduction to Engineering course at Arizona State University supports this approach by teaching students the basics of autonomous maze traversing algorithms and using ASU VIPLE, a Visual Programming Language developed to connect with and direct real-world robots. However, some startup time is needed to learn how to interface with these robots using ASU VIPLE. That is why the HTML5 Autonomous Robot Web Simulator was created -- by encouraging students to use the simulator the problem solving behind autonomous maze traversing algorithms can be introduced more quickly and with immediate affirmation. Our goal was to improve this simulator and add features so that the simulator could be accessed and used for a more wide variety of introductory Computer Science lessons. Features scattered across past implementations of robotic simulators were aggregated in a cross platform solution. Upon initial development, a classroom test group revealed usability concerns and a demonstration of students' mental models. Mean time for task completion was 8.1min - compared to 2min for the authors. The simulator was updated in response to test group feedback and new instructor requirements. The new implementation reduces programming overhead while maintaining a learning environment with support for even the most complex applications.
ContributorsRodewald, Spencer (Co-author, Co-author) / Patel, Ankit (Co-author) / Chen, Yinong (Thesis director) / Chattin, Linda (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This thesis covers second language acquisition in regards to age, examining the difference between elementary and high school students. The primary language of all the students tested was English. The second language being tested in this study is German. The general age range in the elementary students observed was 7-12 years old. The high school students' ages were between 14-18 years old. The environment consisted of a physical education atmosphere, which includes: gyms, outside recreational areas, fitness equipment, fields, etc. Methods used to conduct this study were visual and auditory/verbal approaches. No direct instruction was provided to the students, they were assessed based on their ability to absorb the information when provided to them indirectly in a traditional classroom atmosphere. In addition, direct instruction is also not conducive to a physical education setting as it has the potential to detract from the necessary lesson content.
ContributorsMarch, Ashley Taylor (Author) / Pangrazi, Connie (Thesis director) / Gilfillan, Daniel (Committee member) / School of International Letters and Cultures (Contributor) / College of Health Solutions (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Classical planning is a field of Artificial Intelligence concerned with allowing autonomous agents to make reasonable decisions in complex environments. This work investigates
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
ContributorsNakhleh, Julia Blair (Author) / Srivastava, Siddharth (Thesis director) / Fainekos, Georgios (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This thesis describes a multi-robot architecture which allows teams of robots to work with humans to complete tasks. The multi-agent architecture was built using Robot Operating System and Python. This architecture was designed modularly, allowing the use of different planners and robots. The system automatically replans when robots connect or disconnect. The system was demonstrated on two real robots, a Fetch and a PeopleBot, by conducting a surveillance task on the fifth floor of the Computer Science building at Arizona State University. The next part of the system includes extensions for teaming with humans. An Android application was created to serve as the interface between the system and human teammates. This application provides a way for the system to communicate with humans in the loop. In addition, it sends location information of the human teammates to the system so that goal recognition can be performed. This goal recognition allows the generation of human-aware plans. This capability was demonstrated in a mock search and rescue scenario using the Fetch to locate a missing teammate.
ContributorsSaba, Gabriel Christer (Author) / Kambhampati, Subbarao (Thesis director) / Doupé, Adam (Committee member) / Chakraborti, Tathagata (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
For those interested in the field of robotics, there are not many options to get your hands on a physical robot without paying a steep price. This is why the folks at BCN3D Technologies decided to design a fully open-source 3D-printable robotic arm. Their goal was to reduce the barrier to entry for the field of robotics and make it exponentially more accessible for people around the world. For our honors thesis, we chose to take the design from BCN3D and attempt to build their robot, to see how accessible the design truly is. Although their designs were not perfect and we were forced to make some adjustments to the 3D files, overall the work put forth by the people at BCN3D was extremely useful in successfully building a robotic arm that is programmed with ease.
ContributorsCohn, Riley (Co-author) / Petty, Charles (Co-author) / Ben Amor, Hani (Thesis director) / Yong, Sze Zheng (Committee member) / Computer Science and Engineering Program (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12