Robotics Commons^™

Model-Based Navigation And Control Of Multirotor Uavs: A Machine Learning Approach, Serhat Sönmez

Electronic Theses and Dissertations

In recent decades, unmanned systems, particularly Unmanned Aerial Vehicles (UAVs), have seen significant advancement and unprecedented growth in military, civilian and public domain applications. Scientists have focused on enhancing UAV navigation and control through cutting-edge technologies and support tools. UAVs find applications in many fields, except military, such as agriculture, infrastructure inspection, wildlife monitoring, search and rescue, emergency response, border protection, to name but a few relevant civilian applications. Given the faster-than-exponential increase of available computational power, learning-based algorithms have emerged as a prominent tool for (real-time) multirotor UAV navigation and control. This dissertation centers around the fusion of conventional …

Robotic Multi-Object Grasping From A Pile: Techniques And Algorithms For Enhanced Dexterity, Tianze Chen

USF Tampa Graduate Theses and Dissertations

As robots become increasingly integrated into real-world applications such as warehousing, fulfillment centers, and manufacturing, the need for efficient and adaptable robotic systems grows. One of the key challenges is enabling robots to grasp multiple objects simultaneously, as this significantly boosts the efficiency of tasks like batch picking, sorting, and object transferring, reducing both time and energy consumption. This dissertation presents a comprehensive multi-object grasping (MOG) pipeline that includes pre-grasp selection, end-pose selection, grasping synergy calculation, and a data-driven model for estimating the number of objects being grasped. Central to this work is the development of the Experience Forest structure, …

If Androids Dream, Are They More Than Sheep?: Westworld, Robots And Legal Rights, Amanda J. Dipaolo

Dialogue: The Interdisciplinary Journal of Popular Culture and Pedagogy

The robot protagonists in HBO’s Westworld open the door to several philosophical and ethical questions, perhaps the most complex being: should androids be granted similar legal protections as people? Westworld offers its own exploration of what it means to be a person and places emphasis on one’s ability to feel and understand pain. With scientists and corporations actively working toward a future that includes robots that can display emotion in a way that can convincingly pass as that of a person’s, what happens when androids pass the Turing test, feel empathy, gain consciousness, are sentient, or develop free will? The …

Prototyping Interactive Tactile Digital Logic Simulations: A Hybrid Approach, Logan Bateman

MS in Computer Science Project Reports

Tactile exhibits are common in museums and on the walls of university halls. However, few (if any) tools exist for creating tactile exhibits for teaching digital logic or computing concepts. This project implemented a framework for creating tactile digital logic simulation exhibits, with a focus on rapid prototyping and distributed architecture. Prototyping allows for fast iteration, with the ability to simulate unlimited hardware components such as buttons, light emitting diodes (LEDs), and other input or output devices. Through the abstraction of implementations and a distributed communication protocol, switching to real hardware is seamless and works in tandem with simulated hardware. …

Three-Dimensional Outdoor Object Detection In Quadrupedal Robots For Surveillance Navigations, Muhammad Hassan Tanveer, Zainab Fatima, Hira Mariam, Tanazzah Rehman, Razvan Cristian Voicu

Faculty Articles

Quadrupedal robots are confronted with the intricate challenge of navigating dynamic environments fraught with diverse and unpredictable scenarios. Effectively identifying and responding to obstacles is paramount for ensuring safe and reliable navigation. This paper introduces a pioneering method for 3D object detection, termed viewpoint feature histograms, which leverages the established paradigm of 2D detection in projection. By translating 2D bounding boxes into 3D object proposals, this approach not only enables the reuse of existing 2D detectors but also significantly increases the performance with less computation required, allowing for real-time detection. Our method is versatile, targeting both bird’s eye view objects …

Advanced Grasping Sensor Technologies For Autonomous Robotic Apple Harvesting Using Tactile Data And Cnns, Chris Bae

College of Engineering Summer Undergraduate Research Program

This research investigates how to achieve an optimal grasp of an apple using a four-finger soft robotic grasper equipped with force-resistive sensors. Specifically, we sought to determine whether a convolutional neural network (CNN) could accurately classify the grasper's state and recommend adjustments ("in," "out," or "good" grasp) based on tactile data from the sensors. Spatiotemporal tactile images were developed from the sensors and fed into our CNN, achieving near 100% accuracy on unseen test data. This work suggests that CNN-based processing of tactile images can be a powerful tool for real-time control of soft robotic grippers.

Computer Vision In A Robotic Arm, Jack Maxwell

College of Engineering Summer Undergraduate Research Program

We used a machine learning-based object detection algorithm to give a robotic arm the ability to "see" with its camera.

Real-Time Robot Pose Estimation For Industry 4.0: Enhancing Motion Validation And Monitoring With A Vision-Based Framework, Jad Samaha

Theses and Dissertations

Amidst the era of Industry 4.0, robots became integral to automated production lines by performing complex tasks with high precision and adapting to changing production needs in real-time. Therefore, ensuring their precise and reliable operation is paramount for maintaining high-quality standards and operational efficiency. This invoked the need for an automated motion validation tool that guarantees accurate program task execution, by detecting deviations or anomalies that may indicate mechanical faults or software errors. Given the exponential advancements in AI, particularly in Computer Vision, a vision-based solution is ideal for ensuring the correct positioning of a robot in real-time. Operating independently …

An International Consensus Panel On The Potential Value Of Digital Surgery, Jamie Erskine, Payam Abrishami, Jean Christophe Bernhard, Richard Charter, Richard Culbertson, Jo Carol Hiatt, Ataru Igarashi, Gretchen Purcell Jackson, Matthew Lien, Guy Maddern, Joseph Soon Yau Ng, Anita Patel, Koon Ho Rha, Prasanna Sooriakumaran, Scott Tackett, Giuseppe Turchetti, Anastasia Chalkidou

School of Public Health Faculty Publications

OBJECTIVES: The use of digital technology in surgery is increasing rapidly, with a wide array of new applications from presurgical planning to postsurgical performance assessment. Understanding the clinical and economic value of these technologies is vital for making appropriate health policy and purchasing decisions. We explore the potential value of digital technologies in surgery and produce expert consensus on how to assess this value. DESIGN: A modified Delphi and consensus conference approach was adopted. Delphi rounds were used to generate priority topics and consensus statements for discussion. SETTING AND PARTICIPANTS: An international panel of 14 experts was assembled, representing relevant …

Dynamic Maze Puzzle Navigation Using Deep Reinforcement Learning, Luisa Shu Yi Chiu

Master's Theses

The implementation of deep reinforcement learning in mobile robotics offers a great solution for the development of autonomous mobile robots to efficiently complete tasks and transport objects. Reinforcement learning continues to show impressive potential in robotics applications through self-learning and biological plausibility. Despite its advancements, challenges remain in applying these machine learning techniques in dynamic environments. This thesis explores the performance of Deep Q-Networks (DQN), using images as an input, for mobile robot navigation in dynamic maze puzzles and aims to contribute to advancements in deep reinforcement learning applications for simulated and real-life robotic systems. This project is a step …

Design And Implementation Of An Inverted Short Baseline Acoustic Positioning System, Jakob Frabosilio

Master's Theses

This document details the design, implementation, testing, and analysis of an inverted short baseline acoustic positioning system. The system presented here is an above-water, air-based prototype for an underwater acoustic positioning system; it is designed to determine the position of remotely-operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs) in the global frame using a method that does not drift over time.

A ground-truth positioning system is constructed using a stacked hexapod platform actuator, which mimics the motion of an AUV and provides the true position of an ultrasonic microphone array. An ultrasonic transmitter sends a pulse of sound towards …

Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Multi-agent systems (MASs) have achieved remarkable success in multi-robot control, intelligent transportation, and multiplayer games, etc. Thorough testing for MAS is urgently needed to ensure its robustness in the face of constantly changing and unexpected scenarios. Existing methods mainly focus on single-agent system testing and cannot be directly applied to MAS testing due to the complexity of MAS. To our best knowledge, there are fewer studies on MAS testing. While several studies have focused on adversarial attacks on MASs, they primarily target failure detection from an attack perspective, i.e., discovering failure scenarios, while ignoring the diversity of scenarios. In this …

Heterogeneous Multi-Robot Person-Following In Constrained Environments, Ori A. Miller

Electronic Theses and Dissertations

Maintaining visibility of a person requires effective systems. Security cameras or ground robots might be ideal, but they often fail in uncontrolled or unknown environments. A single ground robot struggles to navigate and track an agent at the same time. This work addresses the challenge by developing a multi-robot system with a slow ground robot and an agile aerial robot. Three methods are evaluated: FORWARD-PF, RL-Person Following (RL), and a baseline closed-loop method. FORWARD-PF proved the most reliable, completing all nine paths and reaching targets nearly twice as fast as RL. Despite completing seven paths, RL faltered on complex tasks. …

Koopman-Based Modeling For Nonlinear Control Of Multirotor Uavs, Simone Martini

Electronic Theses and Dissertations

This PhD dissertation focuses on adopting the emerging Koopman Operator theory for modeling and nonlinear control of multirotor UAVs, focusing specifically on quadrotors for proof-of-concept demonstration purposes.

The Koopman Operator theory is based on the foundation that nonlinear dynamics in the state space may be represented as a linear evolution of some functions in the state space. Thus, using appropriately defined and possibly nonlinear functions of the state variables, called observables, as a new and maybe infinite set of coordinates that are referred to as lifted space, the original nonlinear dynamics appear to be linear. The implications of this theory …

Robotic Odor Source Localization Using Vision And Olfaction Sensing, Sunzid Hassan

Master's Theses

Robotic Odor Source Localization (ROSL) technology allows autonomous agents like robots to find an odor source in unknown environments. A successful odor source location depends crucially on an effective navigation algorithm that directs the robot towards the odor source. This thesis is a combination of three projects. First, we detail development of a versatile multi-modal robotic platform for ROSL real-world ROSL experimentation and discussed real-world validation of a traditional olfactionbased ROSL algorithm. Secondly, we introduced vision in ROSL by proposing a fusion navigation algorithm that integrates deep-learning enabled vision and olfaction-based navigation. This hybrid approach tackles challenges such as turbulent …

Uav-Based Tracking And Following Of Railroad Lines, Keith Michael Lewandowski

Theses and Dissertations

Given the pivotal role of the railroad industry in modern transportation and the potential risks associated with track malfunctions, the inspection and maintenance of railroad tracks emerges as a critical concern. While existing solutions excel in performing accurate measurements and detection, they often rely on large, expensive, and time-consuming platforms for inspections. This project, however, seeks to solve the same problem with the use of an unmanned aerial vehicle (UAV), significantly reducing time and cost while maintaining detection capabilities. In particular, this solution is ideal for large-scale, high-level inspections following major events such as floods [6], hurricanes [7] or earthquakes …

A Personalized Chat Application For Career Profiling: A Case Study, Dhiraj Choithramani

Harrisburg University Dissertations and Theses

Artificial intelligence (AI) has rapidly transformed numerous fields over the past decade, significantly influencing industries such as software engineering and computer science. One of the most impactful developments in this area is the rise of AI-driven chat applications, which have evolved from simple, rule-based systems to sophisticated platforms capable of simulating human-like conversations. These chatbots are increasingly being utilized across various sectors, including customer service, healthcare, and education, to provide users with quick, personalized responses. This research paper presents a case study of a personalized chat application designed specifically for career profiling, leveraging advanced AI technologies to deliver contextually relevant …

Adaptive Robot Collaboration Using Robotic Skin And Motion Similarity., Jordan Dowdy

Electronic Theses and Dissertations

An essential part of robotics research is human-robot collaboration, which enables the use of current and new robots in everyday life and the workforce. This research applies to both parts of human-robot collaboration: physical human-robot interaction (pHRI), as well as non-physical human-robot interaction. The physical interaction uses tactile sensors and a Neuroadaptive Controller (NAC) to allow for the guidance of a robotic arm and its end-effector. The non-physical interaction uses a novel motion similarity metric, the Cartesian Segment Online Dynamic Time-Warping (SODTW), to allow a robot to better adapt to the speed of the user performing the motion during imitation …

Using Efficient Vision Transformers To Improve Perception Systems In Autonomous Off-Road Vehicles, Adam S. Pickeral

All Theses

The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also be quick to make decisions. In Autonomous Vehicle research, the environment perception system is one of the key com- ponents of development. The environment perception system allows the vehicle to understand its surroundings using cameras, light detection and ranging (LiDAR), and other sensor systems or modalities. Deep learning computer vision algorithms have shown to be the …

Development And Implementation Of A Gps-Agnostic Drone Localization System, Alex Peterson

Boise State University Theses and Dissertations

This research develops a GPS-denied state estimation system to localize and orient a drone for touch-based installations on power line towers and cables. As opposed to environments like underground tunnels or building interiors, our system effectively identifies and utilizes sparse landmarks such as towers, cables, and ground features. Our approach utilizes Simultaneous Localization and Mapping (SLAM) to create and reference three-dimensional maps in real time. Specifically, we employ Georgia Tech Smoothing and Mapping (GTSAM), proposed by Georgia Tech's BORG Lab, a factor graph-based data structure consisting of measurement factors and unknown pose variables that we are implementing for solving the …