Computer Engineering Commons^™

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 …

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 …

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

Collaborative Human-Machine Interfaces For Mobile Manipulators., Shamsudeen Olawale Abubakar

Electronic Theses and Dissertations

The use of mobile manipulators in service industries as both agents in physical Human Robot Interaction (pHRI) and for social interactions has been on the increase in recent times due to necessities like compensating for workforce shortages and enabling safer and more efficient operations amongst other reasons. Collaborative robots, or co-bots, are robots that are developed for use with human interaction through direct contact or close proximity in a shared space with the human users. The work presented in this dissertation focuses on the design, implementation and analysis of components for the next-generation collaborative human machine interfaces (CHMI) needed for …

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 …

Distance-Based Formation Control Using Decentralized Sensing With Infrared Photodiodes, Steven Williams

LSU Master's Theses

This study presents an onboard sensor system for determining the relative positions of mobile robots, which is used in decentralized distance-based formation controllers for multi-agent systems. This sensor system uses infrared photodiodes and LEDs; its effective use requires coordination between the emitting and detecting robots. A technique is introduced for calculating the relative positions based on photodiode readings, and an automated calibration system is designed for future maintenance. By measuring the relative positions of their neighbors, each robot is capable of running an onboard formation controller, which is independent of both a centralized controller and a global positioning-like system (e.g., …

Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le

Master's Theses

In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the …

A Low-Cost Experimental Testbed For Multi-Agent System Coordination Control, Victor Fernandez-Kim

LSU Master's Theses

A multi-agent system can be defined as a coordinated network of mobile, physical agents that execute complex tasks beyond their individual capabilities. Observations of biological multi-agent systems in nature reveal that these ``super-organisms” accomplish large scale tasks by leveraging the inherent advantages of a coordinated group. With this in mind, such systems have the potential to positively impact a wide variety of engineering applications (e.g. surveillance, self-driving cars, and mobile sensor networks). The current state of research in the area of multi-agent systems is quickly evolving from the theoretical development of coordination control algorithms and their computer simulations to experimental …

A Continous Rotary Actuation Mechanism For A Powered Hip Exoskeleton, Matthew C. Ryder

Masters Theses

This thesis presents a new mechanical design for an exoskeleton actuator to power the sagittal plane motion in the human hip. The device uses a DC motor to drive a Scotch yoke mechanism and series elasticity to take advantage of the cyclic nature of human gait and to reduce the maximum power and control requirements of the exoskeleton. The Scotch yoke actuator creates a position-dependent transmission that varies between 4:1 and infinity, with the peak transmission ratio aligned to the peak torque periods of the human gait cycle. Simulation results show that both the peak and average motor torque can …

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

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 …

Caddy: A 2005 Roborodentia Entry With Vision And Path Planning Abilities, Taylor Braun-Jones

Computer Engineering

Roborodentia is an autonomous robotics competition held each year during Cal Poly’s Open House. For the 2005 competition, robot entries needed to navigate a maze searching for three randomly placed golf balls, collect them, and then deposit the balls in the “nest” at the end of the maze. A newly added aspect for the 2005 competition included two bonus balls that were placed on a platform behind the wall in two predetermined corners of the maze.

Caddy is a robot that was entered into the 2005 Roborodentia competition. Caddy included a vision system that allowed searching for balls down untraveled …

Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas

George J. Pappas

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …

Adaptive Robot Deployment Algorithms, Jerome Le Ny, George J. Pappas

George J. Pappas

In robot deployment problems, the fundamental issue is to optimize a steady state performance measure that depends on the spatial configuration of a group of robots. For static deployment problems, a classical way of designing high- level feedback motion planners is to implement a gradient descent scheme on a suitably chosen objective function. This can lead to computationally expensive deployment algorithms that may not be adaptive to uncertain dynamic environments. We address this challenge by showing that algorithms for a variety of deployment scenarios in stochastic environments and with noisy sensor measurements can be designed as stochastic gradient descent algorithms, …

Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas

George J. Pappas

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …

Adaptive Robot Deployment Algorithms, Jerome Le Ny, George J. Pappas

George J. Pappas

In robot deployment problems, the fundamental issue is to optimize a steady state performance measure that depends on the spatial configuration of a group of robots. For static deployment problems, a classical way of designing high- level feedback motion planners is to implement a gradient descent scheme on a suitably chosen objective function. This can lead to computationally expensive deployment algorithms that may not be adaptive to uncertain dynamic environments. We address this challenge by showing that algorithms for a variety of deployment scenarios in stochastic environments and with noisy sensor measurements can be designed as stochastic gradient descent algorithms, …

Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas

George J. Pappas

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …

Adaptive Robot Deployment Algorithms, Jerome Le Ny, George J. Pappas

George J. Pappas

In robot deployment problems, the fundamental issue is to optimize a steady state performance measure that depends on the spatial configuration of a group of robots. For static deployment problems, a classical way of designing high- level feedback motion planners is to implement a gradient descent scheme on a suitably chosen objective function. This can lead to computationally expensive deployment algorithms that may not be adaptive to uncertain dynamic environments. We address this challenge by showing that algorithms for a variety of deployment scenarios in stochastic environments and with noisy sensor measurements can be designed as stochastic gradient descent algorithms, …

A Study Of A Novel Modular Variable Geometry Frame Arranged As A Robotic Surface, Christopher James Salisbury

UNLV Theses, Dissertations, Professional Papers, and Capstones

The novel concept of a "variable geometry frame" is introduced and explored through a three-dimensional robotic surface which is devised and implemented using triangular modules. The link design is optimized using surplus motor dimensions as firm constraints, and round numbers for further arbitrary constraints. Each module is connected by a passive six-bar mechanism that mimics the constraints of a spherical joint at each triangle intersection. A three dimensional inkjet printer is used to create a six-module prototype designed around surplus stepper motors powered by an old computer power supply as a proof-of-concept example.

The finite element method is applied to …

Multiple Robot Boundary Tracking With Phase And Workload Balancing, Michael Jay Boardman

Master's Theses

This thesis discusses the use of a cooperative multiple robot system as applied to distributed tracking and sampling of a boundary edge. Within this system the boundary edge is partitioned into subsegments, each allocated to a particular robot such that workload is balanced across the robots. Also, to minimize the time between sampling local areas of the boundary edge, it is desirable to minimize the difference between each robot’s progression (i.e. phase) along its allocated sub segment of the edge. The paper introduces a new distributed controller that handles both workload and phase balancing. Simulation results are used to illustrate …

Variable Structure End Point Control Of A Flexible Manipulator, Shailaja Chenumalla, Sahjendra N. Singh

Electrical & Computer Engineering Faculty Research

We treat the question of control and stabilization of the elastic multibody system developed in the Phillips Laboratory, Edwards Air Force Base, California. The controlled output is judiciously chosen such that the zero dynamics are stable or almost stable. A variable structure control (VSC) law is derived for the end point trajectory control. Although, the VSC law accomplishes precise end point tracking, elastic modes are excited during the maneuver of the arm. A Linear stabilizer is designed for the final capture of the terminal state.