Robotics Commons^™

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. …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …