Computer Engineering 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 …

A Study Of Deep Reinforcement Learning In Autonomous Racing Using Deepracer Car, Mukesh Ghimire

Honors Theses

Reinforcement learning is thought to be a promising branch of machine learning that has the potential to help us develop an Artificial General Intelligence (AGI) machine. Among the machine learning algorithms, primarily, supervised, semi supervised, unsupervised and reinforcement learning, reinforcement learning is different in a sense that it explores the environment without prior knowledge, and determines the optimal action. This study attempts to understand the concept behind reinforcement learning, the mathematics behind it and see it in action by deploying the trained model in Amazon's DeepRacer car. DeepRacer, a 1/18^th scaled autonomous car, is the agent which is trained …

Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor

Dissertations, Master's Theses and Master's Reports

As technology advances, the use of collaborative autonomous mobile systems for various applications will become evermore prevalent. One interesting application of these multi-agent systems is for autonomous mobile microgrids. These systems will play an increasingly important role in applications such as military special operations for mobile ad-hoc power infrastructures and for intelligence, surveillance, and reconnaissance missions. In performing these operations with these autonomous energy assets, there is a crucial need to optimize their functionality according to their specific application and mission. Challenges arise in determining mission characteristics such as how each resource should operate, when, where, and for how long. …

Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports

Many future robotic applications such as the operation in large uncertain environment depend on a more autonomous robot. The robotics long term autonomy presents challenges on how to plan and schedule goal locations across multiple days of mission duration. This is an NP-hard problem that is infeasible to solve for an optimal solution due to the large number of vertices to visit. In some cases the robot hardware constraints also adds the requirement to return to a charging station multiple times in a long term mission. The uncertainties in the robot model and environment require the robot planner to account …

Application Of Advanced Algorithms And Statistical Techniques For Weed-Plant Discrimination, Saman Akbar Zadeh

Theses: Doctorates and Masters

Precision agriculture requires automated systems for weed detection as weeds compete with the crop for water, nutrients, and light. The purpose of this study is to investigate the use of machine learning methods to classify weeds/crops in agriculture. Statistical methods, support vector machines, convolutional neural networks (CNNs) are introduced, investigated and optimized as classifiers to provide high accuracy at high vehicular speed for weed detection.

Initially, Support Vector Machine (SVM) algorithms are developed for weed-crop discrimination and their accuracies are compared with a conventional data-aggregation method based on the evaluation of discrete Normalised Difference Vegetation Indices (NDVIs) at two different …

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan

Dissertations

Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The …

Mechanical Design And Optimization Of An Interactive Animatronic Bald Eagle, Eric Burns

Phi Kappa Phi Research Symposium (2012-2016)

Animatronics is a specialized sub-category of mechatronics, a fusion of mechanical and electrical engineering. The field has grown from small, individual projects into a major industry. As animatronics progress, mechanical engineers are pushed to design internal structures which occupy ever-decreasing spaces and to ensure designs can undergo maintenance and modifications smoothly. This research investigates methods of reducing space required for mechanisms and several other beneficial methods of development as well as varying satisfactions for audiences when exposed to actor-controlled systems rather than pre-scripted functions. The mechanical systems are designed using CAD software available at Georgia Southern. On-campus, resources are used …

Kinematic Control Of Redundant Mobile Manipulators, Mustafa Mashali

USF Tampa Graduate Theses and Dissertations

A mobile manipulator is a robotic arm mounted on a robotic mobile platform. In such a system, the degrees of freedom of the mobile platform are combined with that of the manipulator. As a result, the workspace of the manipulator is substantially extended. A mobile manipulator has two trajectories: the end-effector trajectory and the mobile platform trajectory. Typically, the mobile platform trajectory is not defined and is determined through inverse kinematics. But in some applications it is important to follow a specified mobile platform trajectory. The main focus of this work is to determine the inverse kinematics of a mobile …

Decentralized Coordination Of Multiple Autonomous Vehicles, Yongcan Cao

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This dissertation focuses on the study of decentralized coordination algorithms of multiple autonomous vehicles. Here, the term decentralized coordination is used to refer to the behavior that a group of vehicles reaches the desired group behavior via local interaction. Research is conducted towards designing and analyzing distributed coordination algorithms to achieve desired group behavior in the presence of none, one, and multiple group reference states.

Decentralized coordination in the absence of any group reference state is a very active research topic in the systems and controls society. We first focus on studying decentralized coordination problems for both single-integrator kinematics and …

The Application Of Neural Networks To Optimal Robot Trajectory Planning, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

Interpolation of minimum jerk robot joint trajectories through an arbitrary number of knots is realized using a hardwired neural network. Minimum jerk joint trajectories are desirable for their similarity to human joint movements and their amenability to accurate tracking. The resultant trajectories are numerical rather than analytic functions of time. This application formulates the interpolation problem as a constrained quadratic minimization problem over a continuous joint angle domain and a discrete time domain. Time is discretized according to the robot controller rate. The neuron outputs define the joint angles (one neuron for each discrete value of time) and the Lagrange …