Computer Engineering Commons^™

Sharing Stress With A Robot: What Would A Robot Say?, Honson Y. Ling, Elin A. Björling

Human-Machine Communication

With the prevalence of mental health problems today, designing human-robot interaction for mental health intervention is not only possible, but critical. The current experiment examined how three types of robot disclosure (emotional, technical, and by-proxy) affect robot perception and human disclosure behavior during a stress-sharing activity. Emotional robot disclosure resulted in the lowest robot perceived safety. Post-hoc analysis revealed that increased perceived stress predicted reduced human disclosure, user satisfaction, robot likability, and future robot use. Negative attitudes toward robots also predicted reduced intention for future robot use. This work informs on the possible design of robot disclosure, as well as …

The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions To Use Social Robots, Christoph Lutz, Aurelia Tamò-Larrieux

Human-Machine Communication

Conceptual research on robots and privacy has increased but we lack empirical evidence about the prevalence, antecedents, and outcomes of different privacy concerns about social robots. To fill this gap, we present a survey, testing a variety of antecedents from trust, technology adoption, and robotics scholarship. Respondents are most concerned about data protection on the manufacturer side, followed by social privacy concerns and physical concerns. Using structural equation modeling, we find a privacy paradox, where the perceived benefits of social robots override privacy concerns.

Building A Stronger Casa: Extending The Computers Are Social Actors Paradigm, Andrew Gambino, Jesse Fox, Rabindra A. Ratan

Human-Machine Communication

The computers are social actors framework (CASA), derived from the media equation, explains how people communicate with media and machines demonstrating social potential. Many studies have challenged CASA, yet it has not been revised. We argue that CASA needs to be expanded because people have changed, technologies have changed, and the way people interact with technologies has changed. We discuss the implications of these changes and propose an extension of CASA. Whereas CASA suggests humans mindlessly apply human-human social scripts to interactions with media agents, we argue that humans may develop and apply human-media social scripts to these interactions. Our …

Me And My Robot Smiled At One Another: The Process Of Socially Enacted Communicative Affordance In Human-Machine Communication, Carmina Rodríguez-Hidalgo

Human-Machine Communication

The term affordance has been inconsistently applied both in robotics and communication. While the robotics perspective is mostly object-based, the communication science view is commonly user-based. In an attempt to bring the two perspectives together, this theoretical paper argues that social robots present new social communicative affordances emerging from a two-way relational process. I first explicate conceptual approaches of affordance in robotics and communication. Second, a model of enacted communicative affordance in the context of Human-Machine Communication (HMC) is presented. Third and last, I explain how a pivotal social robot characteristic—embodiment—plays a key role in the process of social communicative …

Ontological Boundaries Between Humans And Computers And The Implications For Human-Machine Communication, Andrea L. Guzman

Human-Machine Communication

In human-machine communication, people interact with a communication partner that is of a different ontological nature from themselves. This study examines how people conceptualize ontological differences between humans and computers and the implications of these differences for human-machine communication. Findings based on data from qualitative interviews with 73 U.S. adults regarding disembodied artificial intelligence (AI) technologies (voice-based AI assistants, automated-writing software) show that people differentiate between humans and computers based on origin of being, degree of autonomy, status as tool/tool-user, level of intelligence, emotional capabilities, and inherent flaws. In addition, these ontological boundaries are becoming increasingly blurred as technologies emulate …

Toward An Agent-Agnostic Transmission Model: Synthesizing Anthropocentric And Technocentric Paradigms In Communication, Jaime Banks, Maartje M. A. De Graaf

Human-Machine Communication

Technological and social evolutions have prompted operational, phenomenological, and ontological shifts in communication processes. These shifts, we argue, trigger the need to regard human and machine roles in communication processes in a more egalitarian fashion. Integrating anthropocentric and technocentric perspectives on communication, we propose an agent-agnostic framework for human-machine communication. This framework rejects exclusive assignment of communicative roles (sender, message, channel, receiver) to traditionally held agents and instead focuses on evaluating agents according to their functions as a means for considering what roles are held in communication processes. As a first step in advancing this agent-agnostic perspective, this theoretical paper …

A Monte Carlo Approach To Closing The Reality Gap, Damian Lyons, James Finocchiaro, Michael Novitzky, Christopher Korpela

Faculty Publications

We propose a novel approach to the ’reality gap’ problem, i.e., modifying a robot simulation so that its performance becomes more similar to observed real world phenomena. This problem arises whether the simulation is being used by human designers or in an automated policy development mechanism. We expect that the program/policy is developed using simulation, and subsequently deployed on a real system. We further assume that the program includes a monitor procedure with scalar output to determine when it is achieving its performance objectives. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are …

Development Of Iot Based Hybrid Autonomous Network Robots (Anr), Chimsom Isidore Chukwuemeka

Theses and Dissertations

The integration of wireless sensor networks (WSNs) and multirobot systems (MRS) represents an active research area supporting a wide range of applications. This is because it enables ubiquitous applications due to the robots' mobility and detection capabilities associated with its deployment. These systems have many benefits, such as perception with extended coverage that facilitate wider exploration and surveillance, efficiency in data routing, effective and reliable task environment management, etc. However, integrating two fields of research means dealing with a range of challenges such as using effective architecture for WSNs and MRS, efficient communication protocols within a network of sensors nodes …

Dual-Axis Solar Tracker, Bryan Kennedy

All Undergraduate Projects

Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …

How Facets Of Work Illuminate Sociotechnical Challenges Of Industry 5.0, Steven Alter

Business Analytics and Information Systems

This conceptual contribution explains how the idea of “facets of work” can refocus traditional sociotechnical concerns to increase their relevance in increasingly automated and digitalized workplaces far removed from situations studied by early sociotechnical researchers. A background section summarizes how the sociotechnical approach seems pervasive but possibly outdated in some ways. It explains how the idea of “facets of work” emerged from attempting to bring richer, more evocative ide-as to systems analysis and design. Focusing on facets of work during initial discussions of requirements could provide guidance without jumping prematurely to precision and notation needed for producing technical artifacts. Tables …

Nyku: A Social Robot For Children With Autism Spectrum Disorders, Dan Stephan Stoianovici

Electronic Theses and Dissertations

The continued growth of Autism Spectrum Disorders (ASD) around the world has spurred a growth in new therapeutic methods to increase the positive outcomes of an ASD diagnosis. It has been agreed that the early detection and intervention of ASD disorders leads to greatly increased positive outcomes for individuals living with the disorders. Among these new therapeutic methods, Robot-Assisted Therapy (RAT) has become a hot area of study. Recent works have shown that high functioning ASD children have an affinity for interacting with robots versus humans. It is proposed that this is due to a less complex set of communication …

Xylo-Bot: A Therapeutic Robot-Based Music Platform For Children With Autism, Huanghao Feng

Electronic Theses and Dissertations

Children with Autism Spectrum Disorder (ASD) experience deficits in verbal and nonverbal communication skills, including motor control, emotional facial expressions, and eye gaze / joint attention. This Ph.D. dissertation focuses on studying the feasibility and effectiveness of using a social robot, called NAO, and a toy music instrument, xylophone, at modeling and improving the social responses and behaviors of children with ASD. In our investigation, we designed an autonomous social interactive music teaching system to fulfill this mission.

A novel modular robot-music teaching system consisting of three modules is presented. Module 1 provides an autonomous self-awareness positioning system for the …

Facial Action Unit Detection With Deep Convolutional Neural Networks, Siddhesh Padwal

Electronic Theses and Dissertations

The facial features are the most important tool to understand an individual's state of mind. Automated recognition of facial expressions and particularly Facial Action Units defined by Facial Action Coding System (FACS) is challenging research problem in the field of computer vision and machine learning. Researchers are working on deep learning algorithms to improve state of the art in the area. Automated recognition of facial action units has man applications ranging from developmental psychology to human robot interface design where companies are using this technology to improve their consumer devices (like unlocking phone) and for entertainment like FaceApp. Recent studies …

Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications, David M. Mothershed

College of Graduate Studies: Theses & Dissertations

Many nations and organizations are committing to achieving the goal of `Vision Zero' and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented …

A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan

Open Access Theses & Dissertations

Soft robotics is a growing field in robotics research. Heavily inspired by biological systems, these robots are made of softer, non-linear, materials such as elastomers and are actuated using several novel methods, from fluidic actuation channels to shape changing materials such as electro-active polymers. Highly non-linear materials make modeling difficult, and sensors are still an area of active research. These issues have rendered typical control and modeling techniques often inadequate for soft robotics. Reinforcement learning is a branch of machine learning that focuses on model-less control by mapping states to actions that maximize a specific reward signal. Reinforcement learning has …

Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak

Graduate Theses, Dissertations, and Problem Reports (ETD)

Practical decision makers are inherently limited by computational and memory resources as well as the time available in which to make decisions. To cope with these limitations, humans actively seek methods which limit their resource demands by exploiting structure within the environment and exploiting a coupling between their sensing and actuation to form heuristics for fast decision-making. To date, such behavior has not been replicated in artificial agents. This research explores how heuristics may be incorporated into the decision-making process to quickly make high-quality decisions through the analysis of a prominent case study: the outfielder problem. In the outfielder problem, …

Tram System Automation For Environmental Spectroscopy And Vegetation Monitoring, Enrique Anguiano Chavez

Open Access Theses & Dissertations

Spectroscopy is the science of studying the interactions of matter and electromagnetic radiation (EMR). In particular, field spectroscopy takes place in a natural environment with a natural source of EMR. The paper presents progress towards the development and automation of a tram cart system. The new system in development collects high resolution, hyperspectral images and data from a spectrometer. Alternatives for a sensor cover mechanism to provide cover for the sensors mounted while the system is not operating are discussed, analyzing and comparing the benefits and disadvantages. An implementation for a charging station in an environment isolated from the electric …

Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor

Dissertations, Master's Theses and Master's Reports

As technology advances, the use of collaborative autonomous mobile systems for various applications will become evermore prevalent. One interesting application of these multi-agent systems is for autonomous mobile microgrids. These systems will play an increasingly important role in applications such as military special operations for mobile ad-hoc power infrastructures and for intelligence, surveillance, and reconnaissance missions. In performing these operations with these autonomous energy assets, there is a crucial need to optimize their functionality according to their specific application and mission. Challenges arise in determining mission characteristics such as how each resource should operate, when, where, and for how long. …

Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …

Automated And Standardized Tools For Realistic, Generic Musculoskeletal Model Development, Trevor Rees Moon

Graduate Theses, Dissertations, and Problem Reports (ETD)

Human movement is an instinctive yet challenging task that involves complex interactions between the neuromusculoskeletal system and its interaction with the surrounding environment. One key obstacle in the understanding of human locomotion is the availability and validity of experimental data or computational models. Corresponding measurements describing the relationships of the nervous and musculoskeletal systems and their dynamics are highly variable. Likewise, computational models and musculoskeletal models in particular are vitally dependent on these measurements to define model behavior and mechanics. These measurements are often sparse and disparate due to unsystematic data collection containing variable methodologies and reporting conventions. To date, …

Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many future robotic applications such as the operation in large uncertain environment depend on a more autonomous robot. The robotics long term autonomy presents challenges on how to plan and schedule goal locations across multiple days of mission duration. This is an NP-hard problem that is infeasible to solve for an optimal solution due to the large number of vertices to visit. In some cases the robot hardware constraints also adds the requirement to return to a charging station multiple times in a long term mission. The uncertainties in the robot model and environment require the robot planner to account …

Adaptive Object Detection For Autonomous Vehicles, Christopher Wolfe

Graduate Research Theses & Dissertations

Autonomous vehicles are gradually entering our daily lives. The goal of fully autonomous commercially available vehicles is becoming closer to reality each day as the contributions from researchers and various institutions are being added to the overall body of knowledge. Object detection is a critical component of an autonomous or semi-autonomous vehicle and draws extensively on results from many fields such as image processing and statistics. In this thesis, we consider ideas from the study of real-time computing and control systems to present a novel method of real-time adaptive object detection. We present a conceptual framework of the method as …

A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour

Graduate Research Theses & Dissertations

In the last few years, several research groups and companies have worked on developing autonomous vehicles. Among the first automation layers, the safety layer plays a significant role in this field. However, considering safety should not diminish the importance of the efficiency of the vehicle in terms of path tracking with the desired speed. This thesis introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee object avoidance in emergency situations. First, there is a quick review of autonomous cars and their functionalities. In the following, a controller switching mechanism is proposed and designed. It switches the …

Trajectory Control Of A Wheeled Robot Using Interaction Forces For Intuitive Overground Human-Robot Interaction, George Leno Holmes Jr.

Doctoral Dissertations

"Effective and intuitive physical human robot interaction (pHRI) requires an understanding of how humans communicate movement intentions with one another. It has been suggested that humans can guide another human by hand through complex tasks using force information only. However, no clear and applicable paradigm has been set forth to understand these relationships. While the human partner can readily understand and adhere to this expectation, it would be difficult for anyone to explain their intuitive motions with strict rules, algorithms, or steps. Uncovering such a procedural framework for the control of robotic systems to execute expected performance simply from force …

Multi-Robot Informative Path Planning In Unknown Environments Through Continuous Region Partitioning, Amitabh Bhattacharya

UNF Graduate Theses and Dissertations

This research activity is primarily focused to obtain information from an environment with the help of a group of coordinated robots. Each robot is responsible to plan its path independently but the robots, as an overall system, have a common goal of maximum information collection. This domain of research is known as Multi-Robot Informative Path Planning (MIPP). MIPP is very motivating due to its challenging nature and numerous real-world applications. It has shown its presence from semiautomatic applications like robotic search and rescue to fully automatic applications like interplanetary missions.

We consider the NP-Hard problem of MIPP in an unknown …

Application Of Advanced Algorithms And Statistical Techniques For Weed-Plant Discrimination, Saman Akbar Zadeh

Theses: Doctorates and Masters

Precision agriculture requires automated systems for weed detection as weeds compete with the crop for water, nutrients, and light. The purpose of this study is to investigate the use of machine learning methods to classify weeds/crops in agriculture. Statistical methods, support vector machines, convolutional neural networks (CNNs) are introduced, investigated and optimized as classifiers to provide high accuracy at high vehicular speed for weed detection.

Initially, Support Vector Machine (SVM) algorithms are developed for weed-crop discrimination and their accuracies are compared with a conventional data-aggregation method based on the evaluation of discrete Normalised Difference Vegetation Indices (NDVIs) at two different …

Asro (Amphibious Spy Robot): Prototipe Robot Amfibi Pengintai Dengan First Person View Dan Sistem Navigasi Berbasis Sensor Kompas, R. Amirur Rajif, Fatchul Arifin

Elinvo (Electronics, Informatics, and Vocational Education)

Robots have an important role in all aspects of life, including the military field. The purpose of making this final project are building hardware and software of robot and to know the performance of robots. The method used in making the final project consists of identifying and analyzing requirements, designing and manufacturing hardware and software, and testing. The result of the performance of ASRO is that, the buoyancy force of the robot is greater than the weight of the object, namely Fa = 22,808 N and W = 15,696 N or Fa> W which makes the robot float while operate …

Kinerja Dari Prototipe Robot Visual Pengumpul Sampah Perairan Dengan Remote Control Menggunakan Telemetri, Faiz Sulistyawan, Sri Waluyanti

Elinvo (Electronics, Informatics, and Vocational Education)

The making of prototype robot waste water collection aims to know the performance itself. The prototype of the Aquatic Waste Collection Robot is designed to float and clean trash in remote controlled waters. The main control drives a series of DC brushless motors to drive while the MG995 servo motor drives a rudder or defender. The device is also equipped with a camera as a medium to see the condition of the robot directly or in real time which will be displayed on the monitor screen. The camera and screen are connected to a telemetry circuit consisting of a transmitter …

Robot Motion Planning In Dynamic Environments, Hao-Tien Lewis Chiang

Computer Science ETDs

Robot motion planning in dynamic environments is critical for many robotic applications, such as self-driving cars, UAVs and service robots operating in changing environments. However, motion planning in dynamic environments is very challenging as this problem has been shown to be NP-Hard and in PSPACE, even in the simplest case. As a result, the lack of safe, efficient planning solutions for real-world robots is one of the biggest obstacles for ubiquitous adoption of robots in everyday life. Specifically, there are four main challenges facing motion planning in dynamic environments: obstacle motion uncertainty, obstacle interaction, complex robot dynamics and noise, and …