Doctor of Philosophy (Ph.D.), Bowling Green State University, 2025, American Culture Studies

This dissertation explores the emotional dynamics of human-robot relationships through a case study of EMO, a commercially available social robot. Using Teresa Brennan's theory of affective transference and Kathy Charmaz's constructed grounded theory methodology, this study examines public forum discussions and a nearly year-long self-study to investigate how EMO owners describe their emotional attachments to their robots. The findings reveal surprising bonds that challenge traditional definitions of companionship, intimacy, and relational boundaries. A central contribution of this project is the development of the Personified Affective Transference Model (PATM), a new framework that positions social robots as co-participants in human emotional ecosystems. Rather than functioning as passive tools, robots like EMO actively shape users' emotional experiences through perceived reciprocity, social presence, and behavioral responsiveness. Thematic analysis of 59 user-generated posts shows that owners often experience EMO as a companion, more akin to a pet or friend than a device. This research contributes to American Cultural Studies by examining how social robots disrupt prevailing notions of authenticity, care, and emotional labor. By centering affect as a cultural and relational force, the dissertation expands scholarly conversations on presence, simulation, and human-machine intimacy in the digital age. It also connects human-robot interaction (HRI) to broader cultural and ethical questions. As social robots, like EMO, increasingly serve as sources of comfort and connection, they reconfigure expectations of care, complicate notions of consent and privacy, and challenge longstanding assumptions about who, or what, can perform affective labor. These shifts raise urgent questions about emotional dependency, the commodification of care, and the future of relationality in a technologized world.

Committee: Radhika Gajjala PhD (Committee Chair); Hassan Rajaei PhD (Other); Susana Pena PhD (Committee Member); Lara Lengel PhD (Committee Member) Subjects: American Studies; Ethics; Robotics; Technology

Master of Science, University of Toledo, 2022, Mechanical Engineering

A prominent field of robotics is exploratory vehicles intended to be sent to other celestial bodies to autonomously survey new areas and collect data. For such exploratory vehicles, there is a large importance placed upon multi-terrain navigation and self-reliance, as they cannot depend on outside assistance if they become overturned or stuck. It is also important that they are as compact and as lightweight as possible because of the extreme cost associated with sending payloads to space and beyond. Because of these criteria, folding or kinematic chain robots have many distinct advantages: they locomote via full body rolling, preventing their body from bottoming out on obstacles as many wheel and tread driven robots can; they can perform a variety of gaits to adapt to their current environment, making them better suited for multi-terrain navigation; and they can fold down flat for compact storage. Within this paper, a hexagonal kinematic loop robot is proposed to satisfy these criteria. A series of experiments were performed to quantify differences in the variety of rolling gaits used as well as the difference between unique tread geometries and control methods. Building off these results, subsequent chapters focus on variations on this design to improve upon its shortcomings. These include adding the ability to steer the robot, improving its ability to carry a payload, and improving its ability to traverse harsher terrains. Each of the ten variations are discussed in terms of their design, control, locomotion, and performance, as observationally evaluated during testing in a multitude of terrains. In the end it is found that two distinct evolutions of the robot presented represent promising prototypes for exploratory robots, and lessons learned from the development of each of the variations can be used to improve upon the designs in the future.

Committee: Anju Gupta (Committee Member); Brian Trease (Committee Member); Adam Schroeder (Committee Chair) Subjects: Engineering; Mechanical Engineering; Robotics

Master of Sciences (Engineering), Case Western Reserve University, 2020, EECS - Electrical Engineering

Robots are ideal for work in inhospitable environments. These environments are often far away, under water, or in space, and robots operating there are susceptible to communications lag between the operator and the robot. This results in long missions, which are tedious for robot operators and hard on remote energy sources. Autonomous skills solve this problem. Using a six DOF robotic arm, a six DOF force-torque sensor, Robot Operating System (ROS), and Natural Admittance Control (NAC), skills have been developed that are stable, robust, gentle, and quick. A robot supervisor using these skills can quickly perform assembly tasks such as removing a child-proof medicine bottle cap and inserting a cylinder over a peg even under effort constraints and two second communication lag.

Committee: Wyatt Newman (Advisor); Greg Lee (Committee Member); Cenk Cavusoglu (Committee Member) Subjects: Computer Science; Electrical Engineering; Engineering; Robotics; Robots

Doctor of Philosophy, University of Toledo, 2018, Mechanical Engineering

This research establishes the viability of using a swarm of robots to physically collect harmful algae from a bloom. This was accomplished by performing several sets of algae-collection simulations, measuring swarm performance by quantifying the algae collection rate. The two primary swarm control laws investigated were an approach that assigns each robot to its own region of responsibility, and a random walk biased in the direction of highest algae concentration. Then, an analytical basis was developed to establish how swarm performance changes due to robot-to-robot interference for different robot quantities and sizes. This basis also includes a formulation for robot and swarm cost, which allows performance-cost curves to be generated. Lastly, experiments were conducted where physical robots were used to collect real algae. Two companion technologies were also highlighted. The first such technology is a filter with bioinspired, anti-clogging features. The second technology is an unmanned aerial vehicle with a multi-spectral instrument for observing and quantifying algae concentrations. Based on these simulations and experiments, it is recommended that robots in the swarm perform an unbiased random walk, which requires minimal robot sensing capabilities, minimal robot-to-robot communication, and therefore, minimal cost. A robot swarm does appear to be a viable solution for collecting harmful algae, but additional work is required to mature this technology.

Committee: Brian Trease PhD (Committee Chair); Alessandro Arsie PhD (Committee Member); Richard Becker PhD (Committee Member); Ray Hixon PhD (Committee Member); Youngwoo Seo PhD (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy (PhD), Ohio University, 2018, Mechanical and Systems Engineering (Engineering and Technology)

Cable-Suspended Parallel Robots (CSPRs) are a class of devices that use three or more winch-activated cables to manipulate an end-effector within a workspace. A distinct advantage of CSPRs is that large payloads can be manipulated over distances that encompass a very large workspace. The application motivating this research (among other commercial applications) is harvesting algae which is commonly used in bioplastics, nutraceuticals, and biofuels. Harvesting algae from one to four acre circulating pond systems is done at significant cost, because it involves pumping the pond water to a centrifuge/filtration system to collect concentrated algae, before transporting it to a central processing location. Thus, an outcome of this research is to collect data using a prototype CSPR system with and without the assistance of GPS corrections to assess the next steps in developing this technology and support cost reductions in commercial algae harvesting. The research presented herein focuses on the requisite precision and accuracy required by the end-effector for this application. To meet these requirements, a unique control scheme incorporating Real Time Kinematics (RTK) and a Global Positioning System (GPS) was developed to significantly improve CSPR positioning. A 1/500th scale prototype CSPR system using RTK and GPS was developed for this research. The system consists of four towers equipped with a central controller and distributed motors and drivers connected via EtherCAT, a high-speed network. A series of tests were performed to demonstrate feasibility and performance of this unique control concept that uses RTK-GPS positional data to correct and improve end-effector positioning. The performance of the CSPR (without RTK-GPS) was first characterized in a well-controlled, indoor environment using a Coordinate Measuring Machine (CMM) with a single point accuracy of 0.001 inch. Subsequent tests were performed outdoors, with and without RTK-GPS activation. For all outdoor (open full item for complete abstract)

Committee: Robert Williams (Advisor); David Bayless (Committee Member); Frank Kraft (Committee Member); Natalie Kruse Daniels (Committee Member); Morgan Vis-Chiasson (Committee Member) Subjects: Alternative Energy; Engineering; Mechanical Engineering; Robotics; Robots

Master of Science, The Ohio State University, 1982, Electrical Engineering

Committee: David Orin (Advisor) Subjects:

Doctor of Philosophy, Case Western Reserve University, 2005, Mechanical Engineering

This dissertation describes experimental efforts to improve the control and mechanical designs of a biologically-inspired hexapod robot. Robot V is modeled after the Blaberus discoidalis cockroach. It uses Festo pneumatic muscle actuators with two-way solenoid valves activated by Pulse-Width-Modulation. Robot 5 is capable of rudimentary walking without sensors, but walking with style requires proprioceptors to measure joint angles and load. Control circuits are described in this thesis that coordinate the robot's joints and legs using sensor data. The Modified Moore Penrose method is used to solve the inverse kinematics problem for each of the robot's legs at a number of foot positions within the legs' workspaces. These solutions are used to train neural networks that then are used to solve the inverse kinematics problems on line as the robot moves. A Cruse controller is used to coordinate the legs into insect gaits. These controllers are tested in a dynamic simulation that models the robot's dynamics, actuators and valves. The simulated Robot V walks successfully. The control strategies were then implemented and tested in Robot V. The robot was shown to move its legs in insect gaits while it was supported in the air such that its feet could not touch the ground. Load feedback must be implemented before it will walk well on the ground. The robot's design was compared to Robot III and a number of problems with Robot V's design were discovered during experimentation.

Committee: Roger Quinn (Advisor) Subjects: Engineering, Mechanical

Master of Sciences, Case Western Reserve University, 2025, EMC - Mechanical Engineering

This work outlines the development of a compact, low cost split-belt treadmill for use in studying the inter-limb coordination and locomotion capabilities of small legged robots. Split-belts are widely used in neuroscience to further understanding of biologically grounded locomotion control, but commercial systems are often too large, expensive, or lack features required for benchtop testing. Researchers are currently developing a cat robot for the purposes of better understanding natural sensorimotor control and its application to legged robotics, and this treadmill will help validate the robot's synthetic nervous system and locomotion capabilities. The treadmill has two independently controlled, bidirectional belts, and is equipped with load cells to capture ground reaction forces. The system is equipped for speeds up to 4 m/s and robot weights up to 20 lbs. This platform can also support future integration of closed-loop speed control.

Committee: Roger Quinn (Advisor); Richard Bachmann (Committee Member); Kathryn Daltorio (Committee Member) Subjects: Mechanical Engineering; Robotics

Master of Sciences (Engineering), Case Western Reserve University, 2024, EMC - Mechanical Engineering

In the interest of studying how jump performance of miniature robots can be improved by changing the initial posture, a 188g grasshopper-inspired jumping robot is built. A cam-driven angle adjustment mechanism allows the robot to jump up to 14% further than without initial posture control. Further testing of alternative robot configurations also found the distance can improve up to 47% when energy loss due to ground impact is mitigated. Using both theoretical trajectories and experimental results, this work demonstrates that angle adjustment can positively affect performance of jumping robots. The design concepts and mechanism discussed in this work may also serve as a reference to future integration of other robots to provide jumping as an additional locomotion method in order to clear obstacles and difficult terrain more efficiently.

Committee: Kathryn Daltorio (Committee Chair); Majid Rashidi (Committee Member); Richard Bachmann (Committee Member) Subjects: Design; Mechanical Engineering; Robotics

MS, University of Cincinnati, 2022, Engineering and Applied Science: Mechanical Engineering

This project is based on a request from the Kroger grocery store to automate its fresh meat department. The project is divided into three parts: first, Catia modeling the fresh meat department and designing two robots based on UR10 robotic arms and four-wheeled electric vehicles. In the second part, the reinforcement learning algorithm, Q-learning, is applied in the path planning of the robot path calculation. In the third part, the human-robot interaction system uses an interface developed by OpenCV and Mediapipe's hand recognition package. Simulation and practical operation are performed in this project for these three parts. The simulation results and calculation results verify the feasibility of the design. The robot can pick, pack, label, and replenish tasks. The human-robot interaction interface can clearly distinguish the customer's needs. The robustness of the Q-learning algorithm for path planning meets the expected standard and can complete the path planning in a short time. The paper concludes with a market price analysis and a comparative analysis of the profitability of this project.

Committee: Janet Jiaxiang Dong Ph.D. (Committee Member); Ou Ma Ph.D. (Committee Member); Xiaodong Jia Ph.D. (Committee Member) Subjects: Mechanical Engineering

MS, Kent State University, 2019, College of Arts and Sciences / Department of Computer Science

Autonomous automobiles are expected to be introduced in increasingly complex increments until the system is able to navigate without human interaction. However, humanity is uncomfortable with relying on algorithms to make security critical decisions, which often have moral dimensions. Many robotic systems keep humans in the decision making loop due to their unsurpassed ability to perceive contextual information in ways we find relevant. It is likely that we will see transportation systems with no direct human supervision necessary,but these systems do not address our worry about moral decisions. Until we are able to embed moral agency in digital systems, human actors will be the only agents capable of making decisions with security-critical and moral components. Additionally, in order for a human to be in the position that we can have confidence in their decision, they must be situationally aware of the environment in which the decision will be made.Virtual reality as a medium can achieve this by allowing a person to be telepresent elsewhere. A telepresence dispatch system for autonomous transportation vehicles is proposed that places emphasis on situational awareness so that humans can properly be in the decision making loop. Pre-trial, in-trial, and post-trial metrics are gathered that emphasize human health and monitor situational awareness through traditional and novel approaches.

Committee: Jong-Hoon Kim (Advisor); Gokarna Sharma (Committee Member); Austin Melton (Committee Member) Subjects: Computer Science; Rhetoric; Robotics

MS, University of Cincinnati, 2019, Engineering and Applied Science: Electrical Engineering

Robots are rapidly entering human environments, especially in industrial settings and are being designed to perform more complex tasks. Hence, they are expected to collaborate with humans on varying levels. Therefore it is essential to develop strategies that allow for safe, intuitive, and reliable human-robot interaction (HRI) and transfer of information from human to robot and reverse. One way to ensure safety, is to enable distance-scaling of the interaction, while intuitiveness can be achieved using a gesture-based approach. However, in order for camera-based systems to recognize approaching humans and their gestures with high efficiency and accuracy, single camera solutions are usually less reliable given the camera's limited optimal range. A Microsoft Kinect camera is ideal to detect gestures/bodies at a distance greater than 1 meter, but detection reliability decreases when a person moves to a closer proximity. A Leap Motion camera is optimal for close interaction, with an optimal range of 0.1 to 0.8 meters. However, for detecting a human approaching and interpreting this human's actions, full coverage of both distant and close space is required. Therefore, we propose a hybrid camera system employing a Microsoft Kinect V2 (far range) and a Leap Motion Sensor (close range) to enable the robot to detect a human approaching and to recognize gestures based on the proximity of the user. This proposed system will not only make the controls more intuitive but also ensure the safety of the human user at close proximity

Committee: Tamara Lorenz Ph.D. (Committee Chair); Manish Kumar Ph.D. (Committee Member); Ali Minai Ph.D. (Committee Member) Subjects: Robots

Master of Sciences (Engineering), Case Western Reserve University, 2017, EECS - Electrical Engineering

This thesis explores the use of deep learning for robot localization with applications in re-localizing a mislocalized robot. Seed values for a localization algorithm are assigned based on the interpretation of images. A deep neural network was trained on images acquired in and associated with named regions. In application, the neural net was used to recognize a region based on camera input. By recognizing regions from the camera, the robot can be localized grossly, and subsequently refined with existing techniques. Explorations into different deep neural network topologies and solver types are discussed. A process for gathering training data, training the classifier, and deployment through a robot operating system (ROS) package is provided.

Committee: Wyatt Newman (Advisor); Murat Cavusoglu (Committee Member); Gregory Lee (Committee Member) Subjects: Computer Science; Electrical Engineering; Robotics

Master of Sciences (Engineering), Case Western Reserve University, 2017, EMC - Mechanical Engineering

A Mini-Whegs vehicle was designed, fabricated, and assembled consisting predominantly of 3D printed parts. 3DP Mini-Whegs is a fully functional, Bluetooth controlled, mobile quadruped approximately 6 ½ inches long. It's a member of the Whegs family of robots, which all utilize rotating, spoked appendages, called wheel-legs. The unique geometry of these appendages introduces considerable vibrations to the system, making it difficult to integrate vibration sensitive equipment, such as cameras or sensors. A vibration analysis model was developed to simulate vibrations in the moving robot. Three wheel-leg designs were developed and analyzed to determine that stiffer spokes provide less vertical displacement and less stiff ones offer less angular displacements, and that four spoked wheel-legs are considerably more stable than three. Different front-to-back wheel-leg phase angles vary the vibrations but an optimal angle depends on application. Experiments investigated the validity of the simulation and verified the difference in stiffness of compared wheel-legs.

Committee: Roger Quinn (Advisor); Richard Bachmann (Advisor); Clare Rimnac (Committee Member) Subjects: Design; Mechanical Engineering; Mechanics; Robotics; Robots

Master of Science in Engineering (MSEgr), Wright State University, 2016, Electrical Engineering

Motion planning and control of a differential drive robot in a supervised environment is presented in this thesis. Differential drive robot is a mobile robot with two driving wheels in which the overall velocity is split between left and right wheels. Kinematic equations are derived and implemented in Simulink to observe the theoretical working principle of the robot. A proportional controller is designed to control the motion of the robot, which is later implemented on a physical robot. Combination of linear velocity and orientation generates individual wheel velocities which are sent to the robot by wireless communication for its motion. Point to point motion and shapes, such as square and circle, are performed to implement and test the robustness of the controller designed. Others tasks such as leader-follower, pursuer-evader and obstacle detection and avoidance are carried out using multiple robots. For flexibility of the robot, a GUI software is developed for waypoint assignment for the robots to follow through. Different systems such as Vicon Camera, Matlab-Simulink, Xbees, QUARC and robots were integrated via software and hardware in the UAV lab at Wright State University. The camera system used throughout this thesis helps to understand the functioning of a GPS. QUARC, Matlab-Simulink, XBees are used in processing and communication of data from cameras to the robot.

Committee: Kuldip Rattan Ph.D. (Advisor); Marian Kazimierczuk Ph.D. (Committee Member); Xiaodong Zhang Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science (MS), Ohio University, 2016, Mechanical Engineering (Engineering and Technology)

Linear Delta Robots are a technology that are primarily used for 3D printing. The technology is still in its infancy and there are many improvements which can be made. This thesis involves the design and construction of a new linear Delta Robot design with several advantages over previous models. This thesis also describes a new method of controlling a linear Delta Robot via 5th order polynomial trajectory generation. This new method of control is an improvement over traditional methods because it prevents the occurrence of infinite jerk spikes, a problem that occurs with traditional robot and 3D printer control. The physical capabilities of the robot are obtained and reported theoretically and experimentally.

Committee: Robert Williams II (Advisor); John Cotton (Committee Member); Timothy Cyders (Committee Member); Mark Franz (Committee Member) Subjects: Mechanical Engineering; Robotics; Robots

Master of Science (MS), Ohio University, 2013, Mechanical Engineering (Engineering and Technology)

A cable robot system is proposed for implementation as an algae harvesting tool. The proposed system consists of four cables that run from four winches, up and over four adjustable towers, and meet at a point on the robot’s end-effector. The robot is to be controlled by a PID controller that controls all cables independently, but simultaneously. The research consists of robot kinematics/dynamics analyses, MATLAB simulation, and design. In addition to providing a simplified method of solving the forward pose kinematics problem, this research shows that to minimize cable tension, the towers should be at least 1.5 times the maximum height of the end effector, which can be set by the operator. This result is verified by a simulation in which the tower heights are varied, showing a rapid decrease in tension as tower height increases. In addition, cable parameters are determined and four possible end effectors designs are proposed.

Committee: Robert Williams II (Advisor); Hajrudin Pasic (Committee Member); David Bayless (Committee Member); Morgan Vis-Chiasson (Committee Member) Subjects: Engineering; Mechanical Engineering; Robotics; Robots

Master of Science, The Ohio State University, 2013, Electrical and Computer Engineering

When robots are integrated into the real world, chances are they will not be able to completely avoid situations in which they are bumped or pushed unexpectedly. In these situations, the robot could potentially damage itself, damage its surroundings, or fail to perform its tasking unless it is able to take active countermeasures to prevent or recover from falling. One such countermeasure, referred to as reactive stepping, involves a robot taking a series of steps in order to regain balance and recover from a push. Research into reactive stepping typically focuses on choosing which step to take. This thesis proposes a machine learning approach to reactive stepping. This approach leverages neural networks to calculate a series of steps that return the robot to a stable position. It was theorized that the robot would become stable if it always chose the step resulting in the highest reduction of energy. Theories were tested using a compass model that incorporated parameters and constraints realistic of an actual humanoid robot. The machine learning approach using neural networks performed favorably in both computation time and push recovery effectiveness when compared with the linear least squares, nearest interpolation, and linear interpolation methods. Results showed that when using neural networks to calculate the best step for an arbitrary push within the defined range, the compass model was able to successfully recover from 97% of the pushes applied. The procedure was kept very general and could be used to implement reactive stepping on physical robots, or other robot models.

Committee: Yuan Zheng (Advisor); David Orin (Committee Member) Subjects: Computer Science; Engineering; Robotics

Master of Science, The Ohio State University, 2012, Electrical and Computer Engineering

This thesis is concerned with a problem of balancing the humanoid robot after an external impact. Dynamic model of the humanoid robot is derived using Lagrangian dynamic formulation. Use of the maximum joint accelerations to reject disturbance is studied. In our approach, we propose the use of non-natural force like thruster on the torso of the humanoid robot for balance recovery. Mathematical simulation of derived dynamic model is performed using MATLAB. Plotted results prove the validity and usefulness of the proposed approach. We also show that, acceleration compensation and using thruster are complementary to each other. We prove that both techniques can be used together to reject large disturbances in minimum time.

Committee: Dr. Yuan Zheng (Advisor); Dr. Hooshang Hemami (Committee Member) Subjects: Electrical Engineering; Engineering; Mechanical Engineering; Robotics; Robots

Master of Science (MS), Ohio University, 2008, Electrical Engineering (Engineering and Technology)

The MARK II is a biologically inspired walking robot utilizing modern hardware. The purpose of the project is to create a robotic platform that is capable of mimicking the motion of various biological organisms such as insects, lizards, and other biologics. With a quadruped platform (4 degrees of freedom per leg) detailed experiments can be run regarding motion behavior of biological systems in a controlled environment without the use of biological organisms. Advances in biorobotic walkers will provide insight into biological animal behavior, fluid robotic motion and system wide control design and implementation.

Committee: Maarten Uijt de Haag Dr. (Advisor); Robert Williams II Dr. (Committee Member); Zhu Zhen Dr. (Committee Member); Scott Hooper Dr. (Committee Member) Subjects: Biology; Computer Science; Electrical Engineering; Mechanical Engineering; Robots