Open Access. Powered by Scholars. Published by Universities.®

Robotics Commons

Open Access. Powered by Scholars. Published by Universities.®

Artificial Intelligence

Discipline
Institution
Publication Year
Publication
Publication Type

Articles 1 - 15 of 15

Full-Text Articles in Robotics

Artificial Sociality, Simone Natale, Iliana Depounti Apr 2024

Artificial Sociality, Simone Natale, Iliana Depounti

Human-Machine Communication

This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …


I Get By With A Little Help From My Bots: Implications Of Machine Agents In The Context Of Social Support, Austin Beattie, Andrew C. High Apr 2022

I Get By With A Little Help From My Bots: Implications Of Machine Agents In The Context Of Social Support, Austin Beattie, Andrew C. High

Human-Machine Communication

In this manuscript we discuss the increasing use of machine agents as potential sources of support for humans. Continued examination of the use of machine agents, particularly chatbots (or “bots”) for support is crucial as more supportive interactions occur with these technologies. Building off extant research on supportive communication, this manuscript reviews research that has implications for bots as support providers. At the culmination of the literature review, several propositions regarding how factors of technological efficacy, problem severity, perceived stigma, and humanness affect the process of support are proposed. By reviewing relevant studies, we integrate research on human-machine and supportive …


A Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell Jan 2022

A Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell

Graduate Research Theses & Dissertations

A fully solid-state, software-defined, one-handed, handle-type control device built around a machine-learning (ML) model that provides intuitive and simultaneous control in position and orientation each in a full three degrees-of-freedom (DOF) is proposed in this paper. The device, referred to as the “Smart Handle”, and it is compact, lightweight, and only reliant on low-cost and readily available sensors and materials for construction. Mobility chairs for persons with motor difficulties could make use of a control device that can learn to recognize arbitrary inputs as control commands. Upper-extremity exoskeletons used in occupational settings and rehabilitation require a natural control device like …


Design Of Plastic Contaminant Eliminator In Seed Cotton, Joshua H. Tandio Dec 2021

Design Of Plastic Contaminant Eliminator In Seed Cotton, Joshua H. Tandio

Theses and Dissertations

Plastic contamination in cotton is a problem in cotton industry and researchers have worked on this problem with different approaches. This thesis documents the design of mechanical and electronic real-time systems for detecting and removing plastic contaminants. The mechanical system was designed to expose plastic embedded inside the seed cotton to the sensor and to separate plastic contaminated cotton from the process stream. The detection system consisted of an embedded computer interfaced with a USB camera and Neural Network (NN) software running in it. Two NN models were tested, a transfer learning model and a built-from-scratch original model. The original …


Our Future Arrived: Diffusion Of Human-Machine Communication And Transformation Of The World For The Post-Pandemic Era, Do Kyun David Kim, Gary Kreps, Rukhsana Ahmed Sep 2021

Our Future Arrived: Diffusion Of Human-Machine Communication And Transformation Of The World For The Post-Pandemic Era, Do Kyun David Kim, Gary Kreps, Rukhsana Ahmed

Human-Machine Communication

The world is getting into a new phase in history. For the first time, humans are verbally communicating and developing meaningful relationships with non-living objects. AI is a wormhole to open a gateway to the new world, and the COVID-19 pandemic prepared the world to transform its system to be an open system that responds to, communicates with, and utilizes the remnants coming out of the wormhole of the new world. Now, we urgently need to create a holistic discourse on how we can recognize, develop, or shape the identities of communicable machines as people develop a partnership with them. …


How Ai Is Socialized To Exhibit Bias, Andrew Treece Aug 2021

How Ai Is Socialized To Exhibit Bias, Andrew Treece

Sociology Student Work Collection

Artificial intelligence is becoming a more prevalent part of our society. This presentation seeks to explore some of the dangers of AI in relation to gender and racial bias from the sociological perspective.


Fatigue Monitoring Through Wearable Sensors For Construction Workers, Srikanth Sagar Bangaru May 2021

Fatigue Monitoring Through Wearable Sensors For Construction Workers, Srikanth Sagar Bangaru

LSU Doctoral Dissertations

About 40% of the US construction workforce experiences high-level fatigue, which leads to poor judgment, increased risk of injuries, a decrease in productivity, and a lower quality of work. Excessive fatigue from working in unpleasant working conditions, long working hours, or heavy workloads can aggravate fatigue's adverse effects, leading to work-related musculoskeletal disorders (WMSDs) and productivity loss. Therefore, it is essential to monitor fatigue to reduce the adverse effects and preventing long-term health problems. However, since fatigue demonstrates itself in several complex processes, there is no single standard measurement method for fatigue detection. This research aims to develop a system …


A Study Of Deep Reinforcement Learning In Autonomous Racing Using Deepracer Car, Mukesh Ghimire May 2021

A Study Of Deep Reinforcement Learning In Autonomous Racing Using Deepracer Car, Mukesh Ghimire

Honors Theses

Reinforcement learning is thought to be a promising branch of machine learning that has the potential to help us develop an Artificial General Intelligence (AGI) machine. Among the machine learning algorithms, primarily, supervised, semi supervised, unsupervised and reinforcement learning, reinforcement learning is different in a sense that it explores the environment without prior knowledge, and determines the optimal action. This study attempts to understand the concept behind reinforcement learning, the mathematics behind it and see it in action by deploying the trained model in Amazon's DeepRacer car. DeepRacer, a 1/18th scaled autonomous car, is the agent which is trained …


Emergency Landing And Guidance System, Joseph Alarid Dec 2020

Emergency Landing And Guidance System, Joseph Alarid

Master's Theses

Every year there are thousands of aviation accidents along with hundreds of human deaths that happen around the world. While the data is sparse, it is well documented that many of these happen from emergency landings gone awry. While pilots can generally make great landings in clear daytime conditions, they are significantly handicapped when it comes to landing at night or amongst poor visibility conditions.

Due to the nature of this problem and some of the large scale advances in software technology we propose a solution that provides a significant improvement from the status quo. Using transfer learning on neural …


Ontological Boundaries Between Humans And Computers And The Implications For Human-Machine Communication, Andrea L. Guzman Feb 2020

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 …


Exploring Cyber-Physical Systems, Misbah Uddin Mohammed Jan 2019

Exploring Cyber-Physical Systems, Misbah Uddin Mohammed

Graduate Research Theses & Dissertations

The advances in IOT, Computer Vision, AI and Machine Learning have made these technologies ubiquitous to our daily lives. From Smart Phones to Connected Vehicles, Cyber Physical systems have been interspersed into everything we interact in today’s world. The aim or this thesis was to explore these advances in Cyber Physical Systems and analyze the different sectors they were affecting. We then hand-picked certain domains and explored further by carrying out practical projects using some of the latest software and hardware resources available. Technologies like Amazon Alexa services, NVIDIA Jetson boards, TensorFlow, OpenCV, NodeJS were heavily employed in our various …


Integration Of Robotic Perception, Action, And Memory, Li Yang Ku Oct 2018

Integration Of Robotic Perception, Action, And Memory, Li Yang Ku

Doctoral Dissertations

In the book "On Intelligence", Hawkins states that intelligence should be measured by the capacity to memorize and predict patterns. I further suggest that the ability to predict action consequences based on perception and memory is essential for robots to demonstrate intelligent behaviors in unstructured environments. However, traditional approaches generally represent action and perception separately---as computer vision modules that recognize objects and as planners that execute actions based on labels and poses. I propose here a more integrated approach where action and perception are combined in a memory model, in which a sequence of actions can be planned based on …


Modeling The Consumer Acceptance Of Retail Service Robots, So Young Song Aug 2017

Modeling The Consumer Acceptance Of Retail Service Robots, So Young Song

Doctoral Dissertations

This study uses the Computers Are Social Actors (CASA) and domestication theories as the underlying framework of an acceptance model of retail service robots (RSRs). The model illustrates the relationships among facilitators, attitudes toward Human-Robot Interaction (HRI), anxiety toward robots, anticipated service quality, and the acceptance of RSRs. Specifically, the researcher investigates the extent to which the facilitators of usefulness, social capability, the appearance of RSRs, and the attitudes toward HRI affect acceptance and increase the anticipation of service quality. The researcher also tests the inhibiting role of pre-existing anxiety toward robots on the relationship between these facilitators and attitudes …


“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams Apr 2016

“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams

Senior Honors Theses

Alan Turing asked if machines can think, but intelligence is more than logic and reason. I ask if a machine can feel pain or joy, have visions and dreams, or paint a masterpiece. The human brain sets the bar high, and despite our progress, artificial intelligence has a long way to go. Studying neurology from a software engineer’s perspective reveals numerous uncanny similarities between the functionality of the brain and that of a computer. If the brain is a biological computer, then it is the embodiment of artificial intelligence beyond anything we have yet achieved, and its architecture is advanced …


Pose Estimation For Robotic Disassembly Using Ransac With Line Features, Shyam Sundar Aswadha Narayanan May 2011

Pose Estimation For Robotic Disassembly Using Ransac With Line Features, Shyam Sundar Aswadha Narayanan

All Theses

In this thesis, a new technique to recognize and estimate the pose of a given 3-D object from a single real image provided known prior knowledge of its approximate structure is proposed. Metrics to evaluate the correctness of a calculated pose are presented and analyzed. The traditional and the more recent approaches used in solving this problem are explored and the various methodologies adopted are discussed.
The first step in disassembling a given assembly from its image is to recognize the attitude and translation of each of its constituent components - a fundamental problem which is being addressed in this …