Engineering Commons^™

Lrtransformer: Learn-Region Transformer For Object-Agnostic Point Cloud Segmentation, Dipesh Gyawali

LSU Master's Theses

3D point cloud segmentation segments the 3D point cloud data into different regions/instances depending on their features that have numerous applications in robotics, autonomous driving, digital twinning, augmented reality, etc. The majority of the existing point cloud segmentation methods depend on class labels to identify 3D objects in the surroundings. Our work focuses on segmenting point clouds into different regions/instances in an object-agnostic manner for any number of objects in the environment. Given the point cloud, our method can segment the entire scene into multiple instances without depending on object shape and size. We leverage the power of the self-attention …

From Curriculum To Career: Analysing The Contribution Of Delft University’S Robotics Msc Programme To The Career Path Of Its Alumni, Gillian Saunders-Smits, Linette Bossen, Joost De Winter

Research Papers

The increasing global demand for robotics expertise led the Delft University of Technology to launch a two-year Master of Science programme in Robotics in 2020. The programme was designed to educate versatile robotics engineers capable of overseeing the entire process from conception of robotics systems to implementation. The curriculum integrates disciplines such as machine perception, artificial intelligence, robot planning and control, human-robot interaction, and ethics, and emphasises personal development through a course called Portfolio, which was later rebranded as Vision and Reflection. The effectiveness of the programme was evaluated by conducting a survey among the first cohort of students. The …

Robotic Origami Worm, Carter Josef, Michael Freeman, Mohammad Hasan

College of Engineering Summer Undergraduate Research Program

Soft robotics can solve many unique engineering problems. The ancient art of origami has inspired design for a new breed of robots. In this research, a novel fold design was created which has high linear stiffness, high bending stiffness, and the ability to deform omnidirectionally in order to turn. The robot is operated using a DC motor to expand and contract and electromagnets to control friction. The robot moves very quickly compared with many other origami robots in the literature. Other interesting ways to control friction were explored including expansion mechanisms. An origami design was created and tested that expands …

Exploring Cognition And Affect During Human-Cobot Interaction, Angelika T. Canete, Javier Gonzalez-Sanchez, Rafael Guerra Silva

College of Engineering Summer Undergraduate Research Program

Collaborative robots (Cobots) have recently gained popularity due to their capability to work collaboratively with human operators. This collaborative relationship has been named under the robotics discipline of Human-Robot Collaboration (HRC), in which humans and robots work together to accomplish a common task while also being in the same physical space. An important part of collaboration is the human's decision-making, which is largely affected by their affective and cognitive state. A cobot lacks this fundamental understanding of the human operator. In this research, we utilize a server-client program to communicate the affective states of a human user to a Raspberry …

Real-Time Length Sensing Of Braided Pneumatic Actuator Using Ir Time-Of-Flight Sensor, Luon B. Chung

Dissertations and Theses

Braided Pneumatic Actuators (BPAs) are used widely in robotics as artificial muscles because of their similar characteristics to biological muscles. When a BPA is pressurized, it expands in the radial direction and contracts in the longitudinal direction. The contraction generates a pulling force that is dependent on the input pressure and BPA length. Biological muscle also behaves in the same way where a pulling force is generated on a contraction. To control BPAs on a robot, the real-time pressure and length measurements are necessary. In this dissertation, I present a new method to measure length of BPAs in real-time using …

A Multi-Aerial Vehicle Platform For Testing Collaborative Mobility Formation Controllers, Matthew Snellgrove

LSU Master's Theses

Multi-agent systems have potential applications in a multitude of fields due to their ability to perform complex tasks with a high degree of robustness. Decentralized systems are multi-agent systems where sensing, control, and communication responsibilities are distributed amongst the agents giving this scheme a particularly high potential for robustness, adaptability, and complexity; however, this comes with its own list of challenges. Formation control is a topic in multi-agent systems that aims to have the agents moving as a virtual rigid body through space. In the literature, there have been successful implementation of formation control algorithms on robot agents in both …

Autonomous Shipwreck Detection & Mapping, William Ard

LSU Master's Theses

This thesis presents the development and testing of Bruce, a low-cost hybrid Remote Operated Vehicle (ROV) / Autonomous Underwater Vehicle (AUV) system for the optical survey of marine archaeological sites, as well as a novel sonar image augmentation strategy for semantic segmentation of shipwrecks. This approach takes side-scan sonar and bathymetry data collected using an EdgeTech 2205 AUV sensor integrated with an Harris Iver3, and generates augmented image data to be used for the semantic segmentation of shipwrecks. It is shown that, due to the feature enhancement capabilities of the proposed shipwreck detection strategy, correctly identified areas have a 15% …

Robust Control Of Contact-Rich Robots Via Neural Bayesian Inference, Nardos Ayele Ashenafi

Boise State University Theses and Dissertations

We provide several data-driven control design frameworks for contact-rich robotic systems. These systems exhibit continuous state flows and discrete state transitions, which are governed by distinct equations of motion. Hence, it is difficult to design a single policy that can control the system in all modes. Typically, hybrid systems are controlled by multi-modal policies, each manually triggered based on observed states. However, as the number of potential contacts increase, the number of policies can grow exponentially and the control-switching scheme becomes too complicated to parameterize. To address this issue, we design contact-aware data-driven controllers given by deep-net mixture of experts. …

Analysis, Measurement, And Modeling Of Millimeter Wave Channels For Aviation Applications, Zeenat Afroze

Theses and Dissertations

Millimeter wave (mmWave) communication systems can employ a large amount of spectrum, and can consequently offer large data rates, e.g., multi-Gigabits-per-second. This technology can be used in many sectors: aviation, vehicles, public transportation, robotics, autonomous factories, etc. Yet mmWave communication systems suffer from some propagation challenges, including large free space path loss (PL), large penetration loss, and large diffraction loss. Hence, it is vital to quantify these and other channel effects to ensure link reliability. Most mmWave systems will employ directional antennas to enable acceptable link distances. In many settings this will require directional receiver antennas to rotate in azimuth …

Gpu-Enabled Genetic Algorithm Optimization And Path Planning Of Robotic Arm For Minimizing Energy Consumption, Yichuan Cao

Theses and Dissertations

The robotic arm represents a complicated mechanical system and advanced engineering principles in robotics, enabling precise and efficient manipulation and interaction with objects in a variety of applications, such as manufacturing, healthcare, space exploration, and other industries. In most cases, energy consumption of robotic tools has been given little consideration due to their perceived insignificance compared to the benefits they offer. However, the increasing capacity demands of factories and the expanding use of robotic arms necessitate careful evaluation and reduction of energy consumption. In this regard, given a task configuration, adjusting the arm's movement path emerges as one of the …

Perspectives On Automation For Omnichannel Services And The Need For New Robotic Solutions For Store Fulfillment Operations, Jennifer Pazour, Manmit Padhy, Georg Fischer, Joyjit Bhowmick, Sebastian Köhler, Gideon Arndt, Kai Furmans

International Material Handling Research Colloquium

No abstract provided.

Underwater Robot Path Planning In An Intermittent Communication System, Hunter Gallant

Dartmouth College Master’s Theses

Sunflower, a novel cross-medium localization system between an aerial drone and an underwater robot, has not yet been implemented in a multi-robot exploration system. This project’s aim was to simulate various configurations of multi-robot systems, and to create an algorithm, called AdjustPath, to improve exploration and avoid inter- robot collisions. With three, five, seven, and ten simulated underwater robots, there was significant improvement when the AdjustPath algorithm was used. Knowing this, future hardware using the Sunflower system could use this proposed algorithm to increase efficiency and avoid more collisions.

Designing The Power System Of A Robot, Nolan Hays

Honors College Theses

This thesis outlines the acquired skills and knowledge acquired through the course of four years of Murray State University’s School of Engineering. The capstone for students in the department was to team up and complete an interdisciplinary senior design project using skills from various tracks of engineering. For this thesis, there is a greater emphasis on the electrical engineering track. The objective of the project was to build an autonomous robot to complete the various tasks within the scope of the IEEE SoutheastCon 2023 Hardware Competition. The robot was controlled via a Raspberry Pi 4 Model B. There were three …

Design And Data-Driven Identification Of A Quadruped Robot, Dakota Rufino

All Theses

The existence of nonlinearities and the lack of sufficient equations are fundamental challenges in modeling, analyzing, and controlling complex systems. However, recent developments revolutionizing the study of dynamical systems. An emerging method in nonlinear dynamical systems is the Koopman operator theory, which provides us with key advantages in performing the modeling, prediction, and control of nonlinear systems. The linear system representation allows us to leverage linear stability analysis. The first section of this thesis briefly covers the construction of a quadrupedal robot, a sufficiently complex nonlinear dynamical system, for the use of analyzing data-driven modeling techniques. The second section details …

Implementation Of Static Rfid Landmarks In Slam For Planogram Compliance, Brennan L. Drake

Honors College Theses

Autonomous robotic systems are becoming increasingly prevalent in everyday life and exhibit robust solutions in a wide range of applications. They face many obstacles with the foremost of which being SLAM, or Simultaneous Localization and Mapping, that encompasses both creation of the map of an unknown environment and localization of the robot in said environment. In this experiment, researchers propose the use of RFID tags in a semi-dynamic commercial environment to provide concrete landmarks for localization and mapping in pursuit of increased locational certainty. With this obtained, the ultimate goal of the research is to construct a robotics platform for …

Claw Hand Activity, Admin Stem For Success, Natalie Wilson

STEM for Success Showcase

Activity plan where students practice coding principles by programming the actions of a claw hand

Dash And Dot Robots, Admin Stem For Success, Natalie Wilson

STEM for Success Showcase

Activity plan using robots to teach students engineering and technology

A Novel Approach For Detection Fault In The Aircraft Exterior Body Using Image Processing, Noura Nayef Almansoori

Theses

The primary objective of this thesis is to develop innovative techniques for the inspection and maintenance of aircraft structures. We aim to streamline the entire process by utilizing images to detect potential defects in the aircraft body and comparing them to properly functioning images of the aircraft. This enables us to determine whether a specific section of the aircraft is faulty or not. We achieve this by employing image processing to train a model capable of identifying faulty images. The image processing methodology we use involves the use of images of both defective and operational parts of the aircraft's exterior. …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Integration Of Real-Time Semantic Building Map Updating With Adaptive Monte Carlo Localization (Amcl) For Robust Indoor Mobile Robot Localization, Matthew Peavy, Pileun Kim, Hafiz Oyediran, Kyungki Kim

Durham School of Architectural Engineering and Construction: Faculty Publications

A robot can accurately localize itself and navigate in an indoor environment based on information about the operating environment, often called a world or a map. While typical maps describe structural layouts of buildings, the accuracy of localization is significantly affected by nonstructural building elements and common items, such as doors, appliances, and furniture. This study enhances the robustness and accuracy of indoor robot localization by dynamically updating the semantic building map with non-structural elements detected by sensors. We propose modified Adaptive Monte Carlo Localization (AMCL), integrating object recognition and map updating into the traditional probabilistic localization. With the proposed …

Combat Robot, Riley Buxton

All Undergraduate Projects

In the sport of combat robotics, the goal is to build a robot that can incapacitate an opposing robot before it becomes incapacitated itself. For this project, a combat robot was designed and tested to compete in Western Allied Robotics’ first competition at Central Washington University. The robot was built to compete in the beetle weight class which means the entire robot had to weigh less than 3 lbs.

To ensure the robot was competitive, a number of important design choices were made. Firstly, an effort was made to ensure that the design was simple and easy to take apart …

Understanding And Quantifying Human Factors In Programming From Demonstration: A User Study Proposal, Shakra Mehak, Aayush Jain, John D. Kelleher, Philip Long, Michael Guilfoyle, Maria Chiara Leva

Conference papers

Programming by demonstration (PbD) is a promising method for robots to learn from direct, non-expert human interaction. This approach enables the interactive transfer of human skills to the robot. As the non-expert user is at the center of PbD, the efficacy of the learned skill is largely dependent on the demonstrations provided. Although PbD methods have been extensively developed and validated in the field of robotics, there has been inadequate confirmation of their effectiveness from the perspective of human teachability. To address this gap, we propose to experimentally investigate the impact of communicating robot learning process on the efficacy of …

Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design, Astrid Van Der Niet, Cilia Claij, Gillian Saunders-Smits

Practice Papers

In 2020, a new two-year MSc programme in robotics was launched. Unlike most existing robotics programmes, which approach robotics from a specific discipline, this programme aims to train multi-deployable robot generalists using a cognitive approach (no hardware creation). The field of robotics is multidisciplinary by nature and educating students on how to approach projects with a multidisciplinary mindset is at the forefront of the programme. Hence, at the end of the first year, students are thrust into experiencing the true multi-disciplinarity of the robotics field in a synthesizing, multidisciplinary project-based course. In this 5 EC course, students work together in …

Incorporating Novel Sensors For Reading Human Health State And Motion Intent Into Real-Time Computing Systems, Adam Sawyer

Masters Theses

"Integrating sensors that read states of the human body into everyday life is an increasing desire, especially with the rise of deep learning which requires vast stores of data to make predictions. This work explores integrating these sensors into the human experience through two methods and recording the results. The first of these methods integrates a MXene based field-effect transistor sensor for the 2019-nCov spike protein with a mobile app. This allows the user to read how saturated their breath is with Covid-19. The second method integrates 3D-printed pressure sensors, and a motion capture system, into a glove to read …

Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. The control scheme is developed by using a singular value decomposition-based direct tracking error-driven approach, which is utilized to derive the weight update laws for the DNN. To avoid catastrophic forgetting in multi-task scenarios and to ensure lifelong learning (LL), a novel online LL scheme based on elastic weight consolidation is included in the DNN weight-tuning laws. Our results demonstrate that the resulting …

Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan

Theses and Dissertations--Mechanical and Aerospace Engineering

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Biologically – Plausible Load Feedback From Dynamically Scaled Robotic Model Insect Legs, William Zyhowski

Graduate Theses, Dissertations, and Problem Reports (ETD)

Researchers have been studying the mechanisms underlying animal motor control for many years using computational models and biomimetic robots. Since testing some theories in animals can be challenging, this approach can enable unique contributions to the field. An example of a system that benefits from this modeling and robotics approach is the campaniform sensillum (CS), a kind of sensory organ used to detect the loads exerted on an insect's legs. The CS on the leg are found in groups on high-stress areas of the exoskeleton and have a major influence on the adaptation of walking behavior. The challenge for studying …

Human Tracking Function For Robotic Dog, Andrew Sharkey

Williams Honors College, Honors Research Projects

With the increase the increase in automation and humans and robots working side by side, there is a need for a more organic way of controlling robots. The goal of this project is to create a control system for Boston dynamics robotic dog Spot that implements human tracking image software to follow humans using computer vision as well as using hand tracking image software to allow for control input through hand gestures.