Engineering Commons^™

Assessing The Alignment Of Social Robots With Trustworthy Ai Design Guidelines: A Preliminary Research Study, Abdikadar Ali, Danielle Thaxton, Ankur Chattopadhyay

Posters-at-the-Capitol

The last couple of years have seen a strong movement supporting the need of having intelligent consumer products align with specific design guidelines for trustworthy artificial intelligence (AI). This global movement has led to multiple institutional recommendations for ethically aligned trustworthy design of the AI driven technologies, like consumer robots and autonomous vehicles. There has been prior research towards finding security and privacy related vulnerabilities within various types of social robots. However, none of these previous works has studied the implications of these vulnerabilities in terms of the robot design aligning with trustworthy AI. In an attempt to address this …

Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang

Doctoral Dissertations and Master's Theses

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.

A. …

Development Of A Model For Control Of A Flexible Production Sewage System, Shalala Jafarova

Scientific-technical journal

This article discusses the development of a production module management model for one area of the technological process. New modeling methods are used for this purpose. Mathematical modeling and research is one of the key issues in the early stages of designing automated and automated systems operating in uncertain or fuzzy environments. Efficient modeling devices are used to solve these problems, taking into account the specific features of the process. The article builds the management model of the production module and obtains the results.

Precision Grasp Planning For Integrated Arm-Hand Systems, Shuwei Qiu

Electronic Thesis and Dissertation Repository

The demographic shift has caused labor shortages across the world, and it seems inevitable to rely on robots more than ever to fill the widening gap in the workforce. The robotic replacement of human workers necessitates the ability of autonomous grasping as the most natural but rather a vital part of almost all activities. Among different types of grasping, fingertip grasping attracts much attention because of its superior performance for dexterous manipulation. This thesis contributes to autonomous fingertip grasping in four areas including hand-eye calibration, grasp quality evaluation, inverse kinematics (IK) solution of robotic arm-hand systems, and simultaneous achievement of …

3d Shape Estimation Of Negative Obstacles Using Lidar Point Cloud Data, Viswadeep Lebakula

Theses and Dissertations

Obstacle detection and avoidance plays a crucial role in the autonomous navigation of unmanned ground vehicles (UGV). Information about the obstacles decreases as the distance between the UGV and obstacles increases. However, this information decreases much more rapidly for negative obstacles than for positive obstacles. UGV navigation becomes more challenging in off-road environments due to the higher probability of finding negative obstacles (e.g., potholes, ditches, trenches, etc.) compared with on-road environments. One approach to solve this problem is to avoid the candidate path with a negative obstacle, but in off-road environments avoiding negative obstacles in all situations is not possible. …

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 …

3d Bionic Arm, Anny Baez Silfa

Publications and Research

Previous work had been done on what was an adaptation of a robotic arm for Roboqueen, which is a persistent research project of the Department of Computer Engineering Technology. This robotic arm consisted of removing the cardboard hands from the Roboqueen and being replaced by 3D printed fingers and wrists to add functionality that did not exist before. Servo motors connected to Arduinos hidden in the forearm will be used to move the fingers and pick up and hold objects in the hand. Currently, the Finger Myoware is an update of the robotic arm in order to understand how prosthetic …

Child Detection System For Preventing Hot-Car Death, Touheda Khanom, Fahmeda Khanom

Publications and Research

According to the Safety Organization Kids and Cars, an average of 38 children die each year from hot cars due to lack of attention from parents. Existing alert system uses sensors that detect child presence and care less about detecting temperature inside the car. In order to save children from heatstroke, our research focuses on providing information about the temperature inside the car using very effective sensors with high precision. In our research, we have tested different sensors and figured out three sensors that can provide precise information about the presence of a child without an adult. Our child detection …

Self Adaptive Reinforcement Learning For High-Dimensional Stochastic Systems With Application To Robotic Control, Sayyed Jaffar Ali Raza

Electronic Theses and Dissertations, 2020-

A long standing goal in the field of artificial intelligence (AI) is to develop agents that can perceive richer problem space and effortlessly plan their activity in minimal duration. Several strides have been made towards this goal over the last few years due to simultaneous advances in compute power, optimized algorithms, and most importantly evident success of AI based machines in nearly every discipline. The progress has been especially rapid in area of reinforcement learning (RL) where computers can now plan-ahead their activities and outperform their human rivals in complex problem domains like chess or Go game. However, despite encouraging …

A Human-Embodied Drone For Dexterous Aerial Manipulation, Dongbin Kim

UNLV Theses, Dissertations, Professional Papers, and Capstones

Current drones perform a wide variety of tasks in surveillance, photography, agriculture, package delivery, etc. However, these tasks are performed passively without the use of human interaction. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply sensing it. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drill into surfaces, and sealing cracks via a drone. This integration with drones will henceforth be known as dexterous aerial manipulation.

Our recent work integrated the worker’s experience into …

Respiratory Compensated Robot For Liver Cancer Treatment: Design, Fabrication, And Benchtop Characterization, Mishek Jair Musa

Graduate Theses and Dissertations

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death in the world. Radiofrequency ablation (RFA) is an effective method for treating tumors less than 5 cm. However, manually placing the RFA needle at the site of the tumor is challenging due to the complicated respiratory induced motion of the liver. This paper presents the design, fabrication, and benchtop characterization of a patient mounted, respiratory compensated robotic needle insertion platform to perform percutaneous needle interventions. The robotic platform consists of a 4-DoF dual-stage cartesian platform used to control the pose of a 1-DoF needle insertion module. The active …

Factors Influencing Service Robot Adoption: A Comparative Analysis Of Hotel-Specific Service Robot Acceptance Models, Ying Dong

UNLV Theses, Dissertations, Professional Papers, and Capstones

The market for service robots is expected to expand significantly owing to the increasing relevance of service automation under the outbreak of the COVID-19 pandemic. Despite the growing managerial interest in robotic applications in the hotel industry, current robotic research has been mostly conceptual with limited robot data on hand. In light of this issue, this paper will conduct a comparative analysis of hotel-specific service robot acceptance models between the Service Robot Acceptance Model (sRAM) and the Service Robot Integration Willingness (SRIW) framework. By identifying key elements of each service robot acceptance model, this paper puts an emphasis on investigating …

Material Handling With Embodied Loco-Manipulation, Jean Chagas Vaz

UNLV Theses, Dissertations, Professional Papers, and Capstones

Material handling is an intrinsic component of disaster response. Typically, first responders, such as firefighters and/or paramedics, must carry, push, pull, and handle objects, facilitating the transportation of goods. For many years, researchers from around the globe have sought to enable full-sized humanoid robots to perform such essential material handling tasks. This work aims to tackle current limitations of humanoids in the realm of interaction with common objects such as carts, wheelbarrows, etc. Throughout this research, many methods will be applied to ensure a stable Zero Moment Point (ZMP) trajectory to allow a robust gait while loco-manipulating a cart. The …

Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar

Electronic Theses and Dissertations

The use of mobile manipulators in service industries as both agents in physical Human Robot Interaction (pHRI) and for social interactions has been on the increase in recent times due to necessities like compensating for workforce shortages and enabling safer and more efficient operations amongst other reasons. Collaborative robots, or co-bots, are robots that are developed for use with human interaction through direct contact or close proximity in a shared space with the human users. The work presented in this dissertation focuses on the design, implementation and analysis of components for the next-generation collaborative human machine interfaces (CHMI) needed for …

Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler

Computer Science and Computer Engineering Undergraduate Honors Theses

Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …

The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

Inverse Kinematics Of The 6dof C12xl, Carl Liu, Lili Ma

Publications and Research

Industrial robotic manipulators are widely used in applications such as pick & place, welding, and assembly to perform repeated tasks in replace of human labor. Such tasks typically require fully autonomous mechanical arms that are capable of identifying the parts to operate, path planning, and trajectory generation & tracking. A robotic arm consists of a sequence of rigid links connected by movable components (the joints). Proper control of the arm’s motion requires the knowledge of inverse kinematics, which computes/outputs the joint variables, i.e., angles for revolute joints and displacement for prismatic joints, causing the robotic arm’s end effector (e.g., gripper, …

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams

USF Tampa Graduate Theses and Dissertations

This dissertation proposes a novel method called state-dependent sensor measurement models (SDSMMs). Such models dynamically predict the state-dependent bias and uncertainty of sensor measurements, ultimately improving fundamental robot tasks such as localization. In our first investigation, we introduced the state-dependent sensor measurement model framework, described their properties, stated the input and output of these models, and described how to train them. We also explained how to integrate such models with an Extended Kalman Filter and a Particle Filter, two popular robot state estimation algorithms. We validated the proposed framework through a series of localization tasks. The results showed that our …

Study On The Implications Of Automomous Ships On Maritime Security And Law Enforcement By Reviewing Maritime Security Incidents, Aditya Pratap Singh

World Maritime University Dissertations

No abstract provided.

Trilateration-Based Localization In Known Environments With Object Detection, Valeria M. Salas Pacheco

USF Tampa Graduate Theses and Dissertations

Many strategies for localization have been proposed, the majority of which rely on distance calculations and estimates. The proposed approach is a method that combines image-based single-camera localization techniques and the principle of trilateration to perform localization in a known indoor environment. By using a camera, the proposed system can detect custom objects using object detection in an indoor environment and calculate an approximation of the camera’s position. To recognize the location, previous information such as the size of the environment and the coordinates and sizes of the objects in the environment are given as input to the system together …

Human-Robot Teaming Configurations: A Study Of Interpersonal Communication Perceptions And Affective Learning In Higher Education, Bryan Abendschein, Chad Edwards, Autumn P. Edwards, Varun Rijhwani, Jasmine Stahl

Journal of Communication Pedagogy

Technology encourages collaboration in creative ways in the classroom. Specifically, social robots may offer new opportunities for greater innovation in teaching. In this study, we combined the established literature on co-teaching teams with the developing field of machine actors used in education to investigate the impressions students had of different team configurations that included both a human and a robot. Participants saw one of three teams composed of a human and a social robot with different responsibilities present a short, prerecorded lecture (i.e., human as lead teacher-robot as teaching assistant, robot as lead teacher-human as teaching assistant, human and robot …

A New Era Of Education: Incorporating Machine Teachers Into Education, Jihyun Kim

Journal of Communication Pedagogy

This editorial briefly discusses the potential of machine agents in education that can assist in creating more positive and meaningful teaching and learning environments. Then, it introduces three articles, two empirical research studies and one research-based instructional activity, compromising a special section on “Machine Teachers in Education” of Journal of Communication Pedagogy. Collectively, these articles help us better understand the role of machines in education and facilitate intellectual dialogues.

Human-Machine Communication: Complete Volume. Volume 3. Diffusion Of Human-Machine Communication During And After The Covid-19 Pandemic

Human-Machine Communication

This is the complete volume of HMC Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemic

What Will Affect The Diffusion Of Ai Agents?, James W. Dearing

Human-Machine Communication

For billions of people, the threat of the Novel Coronavirus SARS-CoV-2 and its variants has precipitated the adoption of new behaviors. Pandemics are radical events that disrupt the gradual course of societal change, offering the possibility that some rapidly adopted innovations will persist in use past the time period of the event and, thus, diffuse more rapidly than in the absence of such an event. Human-machine communication includes a range of technologies with which many of us have quickly become more familiar due to stay-athome orders, distancing, workplace closures, remote instruction, home-bound entertainment, fear of contracting COVID-19, and boredom. In …

The Role Of Vidura Chatbot In The Diffusion Of Knowcovid-19 Gateway, Kerk F. Kee, Prasad P. Calyam, Hariharan Regunath

Human-Machine Communication

The COVID-19 pandemic is an unprecedented global emergency. Clinicians and medical researchers are suddenly thrown into a situation where they need to keep up with the latest and best evidence for decision-making at work in order to save lives and develop solutions for COVID-19 treatments and preventions. However, a challenge is the overwhelming numbers of online publications with a wide range of quality. We explain a science gateway platform designed to help users to filter the overwhelming amount of literature efficiently (with speed) and effectively (with quality), to find answers to their scientific questions. It is equipped with a chatbot …

Communicative Development And Diffusion Of Humanoid Ai Robots For The Post-Pandemic Health Care System, Do Kyun David Kim, Gary Kreps, Rukhsana Ahmed

Human-Machine Communication

As humanoid robot technology, anthropomorphized by artificial intelligence (AI), has rapidly advanced to introduce more human-resembling automated robots that can communicate, interact, and work like humans, we have begun to expect active interactions with Humanoid AI Robots (HAIRs) in the near future. Coupled with the HAIR technology development, the COVID-19 pandemic triggered our interest in using health care robots with many substantial advantages that overcome critical human vulnerabilities against the strong infectious COVID-19 virus. Recognizing the tremendous potential for the active application of HAIRs, this article explores feasible ways to implement HAIRs in health care and patient services and suggests …

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. …

Sabr: Development Of A Neuromorphic Balancing Robot, Alec Yen, Yaw Mensah, Mark Dean

EURēCA: Exhibition of Undergraduate Research and Creative Achievement

We discuss the development of a self-adjusted balancing robot (SABR) using a neuromorphic computing framework for control. Implementations of two-wheeled balancing robots have been achieved using traditional algorithms, often in the form of proportional-integral-derivative (PID) control. We aim to achieve the same task using a neuromorphic architecture, which offers potential for higher power efficiency than conventional processing techniques. We utilize evolutionary optimization (EO) and the second iteration of Dynamic Adaptive Neural Network Arrays (DANNA2) developed by the Laboratory of Tennesseans Exploring Neural Networks (TENNLab). For the purpose of comparison, a traditional balancing robot was first designed using PID control; the …

Cooperative Localization Between Robots Using Vision And Path Planning Algorithm, Charles Koduru

Symposium of Student Scholars

The aim of this article is to provide an obstacle avoidance solution for navigating a robot from one point to another. The robots that are being considered are the NAOHumanoid robot and the wheeled robot Rosbot 2.0. This article's main purpose is to understand how robots work together to minimize positioning errors. The image processing robot (NAO) will be able to instruct the wheeled bot (Rosbot) to navigate around obstacles more accurately by incorporating Inverse Perspective Mapping methods (IPM) and the A-Star Algorithm. This approach demonstrates the ability to improve robot collaboration in order to diagnose various collisions and develop …

Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao

Dissertations

The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles …