Matching Items (24)
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- All Subjects: robotics
- Creators: Computer Science and Engineering Program
- Creators: Artemiadis, Panagiotis
- Creators: Foy, Joseph
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
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
This thesis focused on understanding how humans visually perceive swarm behavior through the use of swarm simulations and gaze tracking. The goal of this project was to determine visual patterns subjects display while observing and supervising a swarm as well as determine what swarm characteristics affect these patterns. As an ultimate goal, it was hoped that this research will contribute to optimizing human-swarm interaction for the design of human supervisory controllers for swarms. To achieve the stated goals, two investigations were conducted. First, subjects gaze was tracked while observing a simulated swarm as it moved across the screen. This swarm changed in size, disturbance level in the position of the agents, speed, and path curvature. Second, subjects were asked to play a supervisory role as they watched a swarm move across the screen toward targets. The subjects determined whether a collision would occur and with which target while their responses as well as their gaze was tracked. In the case of an observatory role, a model of human gaze was created. This was embodied in a second order model similar to that of a spring-mass-damper system. This model was similar across subjects and stable. In the case of a supervisory role, inherent weaknesses in human perception were found, such as the inability to predict future position of curved paths. These findings are discussed in depth within the thesis. Overall, the results presented suggest that understanding human perception of swarms offers a new approach to the problem of swarm control. The ability to adapt controls to the strengths and weaknesses could lead to great strides in the reduction of operators in the control of one UAV, resulting in a move towards one man operation of a swarm.
ContributorsWhitton, Elena Michelle (Author) / Artemiadis, Panagiotis (Thesis director) / Berman, Spring (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
This thesis focused on grasping tasks with the goal of investigating, analyzing, and quantifying human catching trends by way of a mathematical model. The aim of this project was to study human trends in a dynamic grasping task (catching a rolling ball), relate those discovered trends to kinematic characteristics of the object, and use this relation to control a robot hand in real time. As an ultimate goal, it was hoped that this research will aide in furthering the bio-inspiration in robot control methods. To achieve the above goal, firstly a tactile sensing glove was developed. This instrument allowed for in depth study of human reactionary grasping movements when worn by subjects during experimentation. This sensing glove system recorded force data from the palm and motion data from four fingers. From these data sets, temporal trends were established relating to when subjects initiated grasping during each trial. Moreover, optical tracking was implemented to study the kinematics of the moving object during human experiments and also to close the loop during the control of the robot hand. Ultimately, a mathematical bio-inspired model was created. This was embodied in a two-term decreasing power function which related the temporal trend of wait time to the ball initial acceleration. The wait time is defined as the time between when the experimental conductor releases the ball and when the subject begins to initiate grasping by closing their fingers, over a distance of four feet. The initial acceleration is the first acceleration value of the object due to the force provided when the conductor throws the object. The distance over which the ball was thrown was incorporated into the model. This is discussed in depth within the thesis. Overall, the results presented here show promise for bio-inspired control schemes in the successful application of robotic devices. This control methodology will ideally be developed to move robotic prosthesis past discrete tasks and into more complicated activities.
ContributorsCard, Dillon (Co-author) / Mincieli, Jennifer (Co-author) / Artemiadis, Panagiotis (Thesis director) / Santos, Veronica (Committee member) / Middleton, James (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
Description
The purpose of this project is to design a waterproof magnetic coupling that will allow the actuators on remotely operated vehicles (ROV) to remain water tight in extreme underwater conditions for longs periods of time. ROVs are tethered mobile robots controlled and powered by an operator from some distance away at the surface of the water. These vehicles all require some method for transmitting power to the surrounding water to interact with their environment, such as in thrusters for propulsion or a claw for manipulation. Many commercially available thrusters, for example, use shaft seals to transfer power through a waterproof housing to the adjacent water. Even though this works excellently for many of them, I propose that having a static seal and transmitting the power from the motor to the shaft through magnetic coupling will allow a much greater depth at which they are waterproof to be achieved. In addition, it will not require the chronic maintenance that dynamic shaft seals entail, making long scientific endeavors possible.
ContributorsHouda, Jonathon Jacob (Author) / Foy, Joseph (Thesis director) / Zhu, Haolin (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
Walking ability is a complex process that is essential to humans, critical for performing a range of everyday tasks and enables a healthy, independent lifestyle. Human gait has evolved to be robust, adapting to a wide range of external stimuli, including variable walking surface compliance. Unfortunately, many people suffer from impaired gait as a result of conditions such as stroke. For these individuals, recovering their gait is a priority and a challenge. The ASU Variable Stiffness Treadmill (VST) is a device that is able to the change its surface compliance through its unique variable stiffness mechanism. By doing this, the VST can be used to investigate gait and has potential as a rehabilitation tool. The objective of this research is to design a variable damping mechanism for the VST, which addresses the need to control effective surface damping, the only form of mechanical impedance that the VST does not currently control. Thus, this project will contribute toward the development of the Variable Impedance Treadmill (VIT), which will encompass a wider range of variable surface compliance and enable all forms of impedance to be con- trolled for the first time. To achieve this, the final design of the mechanism will employ eddy current damping using several permanent magnets mounted to the treadmill and a large copper plate stationed on the ground. Variable damping is obtained by using lead screw mechanisms to remove magnets from acting on the copper plate, which effectively eliminates their effect on damping and changes the overall treadmill surface damping. Results from experimentation validate the mechanism's ability to provide variable damping to the VST. A model for effective surface damping is generated based on open-loop characterization experiments and is generalized for future experimental setups. Overall, this project progresses to the development of the VIT and has potential applications in walking surface simulation, gait investigation, and robot-assisted rehabilitation technology.
ContributorsFou, Linda Guo (Author) / Artemiadis, Panagiotis (Thesis director) / Lee, Hyunglae (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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
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