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Articles 1 - 14 of 14
Full-Text Articles in Robotics
Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang
Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang
Electronic Theses and Dissertations
Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large …
Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding
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 Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell
A Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell
Graduate Research Theses & Dissertations
A fully solid-state, software-defined, one-handed, handle-type control device built around a machine-learning (ML) model that provides intuitive and simultaneous control in position and orientation each in a full three degrees-of-freedom (DOF) is proposed in this paper. The device, referred to as the “Smart Handle”, and it is compact, lightweight, and only reliant on low-cost and readily available sensors and materials for construction. Mobility chairs for persons with motor difficulties could make use of a control device that can learn to recognize arbitrary inputs as control commands. Upper-extremity exoskeletons used in occupational settings and rehabilitation require a natural control device like …
Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao
Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao
Dissertations
The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles …
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
Electrical and Computer Engineering Faculty Publications
Advances in machine learning technologies in recent years have facilitated developments in autonomous robotic systems. Designing these autonomous systems typically requires manually specified models of the robotic system and world when using classical control-based strategies, or time consuming and computationally expensive data-driven training when using learning-based strategies. Combination of classical control and learning-based strategies may mitigate both requirements. However, the performance of the combined control system is not obvious given that there are two separate controllers. This paper focuses on one such combination, which uses gravity-compensation together with reinforcement learning (RL). We present a study of the effects of gravity …
Lawn Buddy, Jayson Johnston, Andrew Brown, Jacob Maljian
Lawn Buddy, Jayson Johnston, Andrew Brown, Jacob Maljian
Electrical Engineering
Grass lawns are a common hallmark of the American home. In 2019, a survey from the National Association of Landscape Professionals found that 81% of all Americans owned a lawn [1]. Mowing is a time consuming and costly chore that is part of maintaining a grass lawn. The manual labor in mowing a lawn can exceed 40 hours per year [2]. People commonly incur weekly costs on mowing services to save time. Traditional gas powered mowers are physically demanding and use engines that need routine maintenance. They operate loudly enough that users should be wearing hearing protection and the noise …
Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor
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. …
An Application Of Sliding Mode Control To Model-Based Reinforcement Learning, Aaron Thomas Parisi
An Application Of Sliding Mode Control To Model-Based Reinforcement Learning, Aaron Thomas Parisi
Master's Theses
The state-of-art model-free reinforcement learning algorithms can generate admissible controls for complicated systems with no prior knowledge of the system dynamics, so long as sufficient (oftentimes millions) of samples are available from the environ- ment. On the other hand, model-based reinforcement learning approaches seek to leverage known optimal or robust control to reinforcement learning tasks by mod- elling the system dynamics and applying well established control algorithms to the system model. Sliding-mode controllers are robust to system disturbance and modelling errors, and have been widely used for high-order nonlinear system control. This thesis studies the application of sliding mode control …
Comparison Of Lqr And Lqr-Mrac For Linear Tractor-Trailer Model, Kevin Richard Gasik
Comparison Of Lqr And Lqr-Mrac For Linear Tractor-Trailer Model, Kevin Richard Gasik
Master's Theses
The United States trucking industry is immense. Employing over three million drivers and traveling to every city in the country. Semi-Trucks travel millions of miles each week and encompass roads that civilians travel on. These vehicles should be safe and allow efficient travel for all. Autonomous vehicles have been discussed in controls for many decades. Now fleets of autonomous vehicles are beginning their integration into society. The ability to create an autonomous system requires domain and system specific knowledge. Approaches to implement a fully autonomous vehicle have been developed using different techniques in control systems such as Kalman Filters, Neural …
Desarrollo De Una Estrategia De Control Predictivo Aplicado A Un Péndulo Invertido, Que Permita La Estabilización De Imágenes En Robots Para Exploración Agrícola, David Mateo Rojas Vallejo
Desarrollo De Una Estrategia De Control Predictivo Aplicado A Un Péndulo Invertido, Que Permita La Estabilización De Imágenes En Robots Para Exploración Agrícola, David Mateo Rojas Vallejo
Ingeniería en Automatización
La robótica es un campo de estudio tan amplio, que se puede extender prácticamente a cualquiera de las labores humanas; una de estas actividades es la agricultura, aunque para que esto se logre, primero se deben considerar factores mas específicos de un sistema robótico como: visión artificial, estructuras robóticas, control de sistemas, entre otros. En este proyecto se desarrolla una estrategia de control para una plataforma de péndulo invertido, que emula el sistema mecánico en donde se posicionaría la cámara de un robot agrícola. El sistema consiste en un péndulo invertido rotativo, y la estrategia de control que se implementó …
Cyber-Physical System Characterization And Co-Regulation Of A Quadrotor Uas, Seth E. Doebbeling
Cyber-Physical System Characterization And Co-Regulation Of A Quadrotor Uas, Seth E. Doebbeling
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
An Unmanned Aircraft System (UAS) is a Cyber-Physical System (CPS) in which a host of real-time computational tasks contending for shared resources must be cooperatively managed to obtain mission objectives. Traditionally, control of the UAS is designed assuming a fixed, high sampling rate in order to maintain reliable performance and margins of stability. But emerging methods challenge this design by dynamically allocating resources to computational tasks, thereby affecting control and mission performance. To apply these emerging strategies, a characterization and understanding of the effects of timing on control and trajectory following performance is required. Going beyond traditional control evaluation techniques, …
Ubot-7: The Design Of A Compliant Dexterous Mobile Manipulator, Jonathan Cummings
Ubot-7: The Design Of A Compliant Dexterous Mobile Manipulator, Jonathan Cummings
Masters Theses
This thesis presents the design of uBot-7, the latest version of a dexterous mobile manipulator. This platform has been iteratively developed to realize a high performance-to-cost dexterous whole body manipulator with respect to mobile manipulation. The semi-anthropomorphic design of the uBot is a demonstrated and functional research platform for developing advanced autonomous perception, manipulation, and mobility tasks. The goal of this work is to improve the uBot’s ability to sense and interact with its environment in order to increase the platforms capability to operate dexterously, through the incorporation of joint torque feedback, and safely, through the implementation of passive and …
Modeling, Analysis, And Control Of A Mobile Robot For In Vivo Fluoroscopy Of Human Joints During Natural Movements, Matthew A. Young
Modeling, Analysis, And Control Of A Mobile Robot For In Vivo Fluoroscopy Of Human Joints During Natural Movements, Matthew A. Young
Doctoral Dissertations
In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while …
Adaptive Nonlinear Control For Autonomous Ground Vehicles, William Spencer Black
Adaptive Nonlinear Control For Autonomous Ground Vehicles, William Spencer Black
Open Access Theses
We present the background and motivation for ground vehicle autonomy, and focus on uses for space-exploration. Using a simple design example of an autonomous ground vehicle we derive the equations of motion. After providing the mathematical background for nonlinear systems and control we present two common methods for exactly linearizing nonlinear systems, feedback linearization and backstepping. We use these in combination with three adaptive control methods: model reference adaptive control, adaptive sliding mode control, and extremum-seeking model reference adaptive control. We show the performances of each combination through several simulation results. We then consider disturbances in the system, and design …