Robotics Commons^™

Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding

Dissertations

In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as …

Outdoor Operations Of Multiple Quadrotors In Windy Environment, Deepan Lobo

Dissertations

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV …

Cloudbots: Autonomous Atmospheric Explorers, Akash Binoj

Honors Scholar Theses

The CloudBot is an autonomous weather balloon that operates on the principle of variable buoyancy to ascend and descend in the atmosphere. This project aims to develop a device that will collect atmospheric measurements and communicate them mid-flight. The apparatus consists of a helium-filled balloon, the robotic payload, and an air cell. The fixed-volume helium balloon at the top provides an upwards buoyancy force, while the air cell at the bottom can hold a variable amount of pressure to adjust the weight of the CloudBot. By doing so, it is able to travel in storm conditions and collect valuable atmospheric …

Du Undergraduate Showcase: Research, Scholarship, And Creative Works: Abstracts, Emma Aggeler, Elena Arroway, Daisy T. Booker, Justin Bravo, Kyle Bucholtz, Megan Burnham, Nicole Choi, Spencer Cockerell, Rosie Contino, Jackson Garske, Kaitlyn Glover, Caroline Hamilton, Haley Hartmann, Madalyne Heiken, Colin Holter, Leah Huzjak, Alyssa Jeng, Cole Jernigan, Chad Kashiwa, Adelaide Kerenick, Emily King, Abigail Langeberg, Maddie Leake, Meredith Lemons, Alec Mackay, Greer Mckinley, Ori Miller, Guy Milliman, Katherine Miromonti, Audrey Mitchell, Lauren Moak, Megan Morrell, Gelella Nebiyu, Zdenek Otruba, Toni V. Panzera, Kassidy Patarino, Sneha Patil, Alexandra Penney, Kevin Persky, Caitlin Pham, Gabriela Recinos, Mary Ringgenberg, Chase Routt, Olivia Schneider, Roman Shrestha, Arlo Simmerman, Alec Smith, Tessa Smith, Nhi-Lac Thai, Kyle Thurmann, Casey Tindall, Amelia Trembath, Maria Trubetskaya, Zachary Vangelisti, Peter Vo, Abby Walker, David Winter, Grayden Wolfe, Leah York

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Showcase.

Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy

Theses and Dissertations

The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility …

The Effects Of Ecological Simulation For Ground Vehicle Mobility Forecasting, Christopher R. Hudson

Theses and Dissertations

Unmanned ground vehicles (UGV) are being explored for use in military domains. Military UGVs operate in complex off-road environments. Vehicle mobility forecasting plays an important role in understanding how and where a vehicle can operate. Traditional mobility forecasting has been done using an analytical model known as the NATO Reference Mobility Model (NRMM). There has been a push to extend the forecasting capabilities of NRMM by integrating more simulation methods. Simulation enables the repeated testing of UGVs in scenarios that would be difficult or dangerous to study in real world testing. To accurately capture UGV performance in simulation, the operating …

Automated Robotic Light Bulb Testing Platform, Agha I. Akram, Muhammad Ali Ummy

Publications and Research

The main purpose of this project is to create a functional prototype of a multilayered system that incorporates aspects of electrical, mechanical, and computer engineering technology. The main objective of the system is to be able to determine whether a light bulb is working or not. The building blocks of this system are a robotic arm that is able to slide along a rail (for added mobility), a conveyor belt, and an electromechanical device that holds and tests light bulbs. Initially, the robot arm picks up a light bulb and places it into the holder which then tests it. A …

Model Based Force Estimation And Stiffness Control For Continuum Robots, Vincent A. Aloi

Doctoral Dissertations

Continuum Robots are bio-inspired structures that mimic the motion of snakes, elephant trunks, octopus tentacles, etc. With good design, these robots can be naturally compliant and miniaturizable, which makes Continuum Robots ideal for traversing narrow complex environments. Their flexible design, however, prevents us from using traditional methods for controlling and estimating loading on rigid link robots.

In the first thrust of this research, we provided a novel stiffness control law that alters the behavior of an end effector during contact. This controller is applicable to any continuum robot where a method for sensing or estimating tip forces and pose exists. …

Designing Autonomous Drone For Food Delivery In Gazebo/Ros Based Environments, Hrishitva Patel

Computer Science and Engineering Research

There has been a growing global trend towards convenience, speed, and ease in delivery services, and this has been further accelerated by the COVID pandemic. With the everincreasing demand for easily accessible deliveries and expanded delivery service coverage, it has become critical that innovations in this space be developed to further ensure the industry’s smooth operation. With the emergence of the COVID-19 pandemic, the inadequacies became more apparent, emphasizing the need to revolutionize and accelerate the trend in order to meet the increased demand. Drone delivery systems are of particular interest in this context because they can enable faster and …

Control, Decision-Making, And Learning Approaches For Connected And Autonomous Driving Systems With Humans-In-The-Loop, Fangjian Li

All Dissertations

By virtue of vehicular connectivity and automation, the vehicle becomes increasingly intelligent and self-driving capable. However, no matter what automation level the vehicle can achieve, humans will still be in the loop despite their roles. First, considering the manual driving car as a disturbance to the connected and autonomous vehicles (CAVs), a novel string stability is proposed for mixed traffic platoons consisting of both autonomous and manual driving cars to guarantee acceptable motion fluctuation and platoon safety. Furthermore, humans are naturally considered as the rider in the passenger vehicle. A human-centered cooperative adaptive cruise control (CACC) is designed to improve …

Autonomous Navigator Mobile Robot Upgrade, David Sansoucy

Thinking Matters Symposium

The mobile robot platform has been developed over the course of 10 years at USM. In Spring 2020, Belle-Isle and Werner updated the previous framework by rewriting the software to use the ROS framework running on an on-board Raspberry Pi 3. They also implemented navigation using an A* motion planning algorithm and image processing. In Summer 2021, Ames incorporated Lidar and Kinect sensors onto the robot to improve its real-time navigation capabilities. He also made improvements to the power distribution systems. This project aimed to build on the ROS frameworks developed by the previous 2 teams with the main goal …

Combat Robot, Wayne Lambert, Elijah Harris, Brian Eiseman, Jordan Meyer

ONU Student Research Colloquium

The senior capstone project that was tasked to the team was the decision of choosing a challenge within a national robotics competition. The group decided to compete at the National Robotics Challenge in Marion, Ohio. The idea was to participate in the combat robot competition at this NRC event. Once this decision had been made the next steps were to get an idea of what the rules and requirements of the competition were and to try and to sketch a very rough drawing of what the ideal robot should look like. From there it was decided to start a timeline …

Development Of A Compliant Gripper Driven By 3 Dof Soft Robot, Derek M. Price Ii, Ricardo Ramirez, Pt Angel Tran

Symposium of Student Scholars

Industrial robots are moving toward automation, which makes it increasingly necessary to replace the functions traditionally performed by humans with robotics. Pick and place operation is a prime example of such automation. Robots that pick up and place objects mimic the human action of picking an object up and placing it in a targeted location. It has led to the development of robotic end-effectors that have a human-like feel. Grippers can be articulated in various ways depending on their application area and well-defined desired tasks. As compliant and soft links deflect more under the same load than their rigid body …

A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert

Student Research

Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …

Putin And Putnam: Interpreting Russian Military Activity Through A Three Player, Two-Level Game, Nathan M. Colvin

Modeling, Simulation and Visualization Student Capstone Conference

Is Vladimir Putin a bad strategist, perhaps irrational? Previous military activity by Russia, such as the annexation of Crimea of 2014, yielded limited international gains, at a significant economic and reputational cost. Yet as the 2022 invasion of Ukraine shows, Putin is willing to commit military power, despite the cost of sanctions and other possible retaliation. This three-player simultaneous game, originally created in June, 2021, demonstrates how domestic and international considerations of President Vladimir Putin might lead to otherwise unpredictable Russian military behavior. In this extended version of Robert Putnam’s “two-level game,” President Putin rationally uses the international venue as …

Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette

Modeling, Simulation and Visualization Student Capstone Conference

Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling …

Real-Time External Labeling For Interactive Visualization In Virtual Environments, Shan Liu, Yuzhong Shen

Modeling, Simulation and Visualization Student Capstone Conference

A real-time external labeling algorithm has been developed to explore the potential for applying annotation and visualization to virtual reality environments, which manages label placement in the projections of virtual 3D models on the view plane. The approach intends to place labels with visual constraints, such as no overlapping, intersections, and occlusions, close proximity to the model parts, by adjusting external annotations' positions concerning available space in the view plane. This algorithm is based on the projected model's contour and adapts to camera viewpoint changes within interactive frame rates. It solves the visibility problem of annotations and operates in real-time …

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Exoskeletons And The Future Of Work: Envisioning Power And Control In A Workforce Without Limits, Gavin L. Kirkwood, J. Nan Wilkenfeld, Norah E. Dunbar

Human-Machine Communication

Exoskeletons are an emerging form of technology that combines the skills of both machines and humans to give wearers the ability to complete physically demanding tasks that would be too strenuous for most humans. Exoskeleton adoption has the potential to both enhance and disrupt many aspects of work, including power dynamics in the workplace and the human-machine interactions that take place. Dyadic Power Theory (DPT) is a useful theory for exploring the impacts of exoskeleton adoption. In this conceptual paper, we extend DPT to relationships between humans and machines in organizations, as well as human-human communication where use of an …

Human-Machine Communication: Complete Volume 4

Human-Machine Communication

This is the complete volume of HMC Volume 4.