Computer Engineering Commons^™

Hardware Implementation Of Assistive Technology Robot, Joycephine Li

Publications and Research

SuperHERO is an on-going research project in Computer Engineering Technology department which involves upgrading Heathkit Education Robot (HERO) hardware circuits and features by using modern hardware devices and sensors. The current phase of the project will focus on upgrading the motor drive system hardware as well as implementation and testing of features such as mobile robot obstacle detection and other assistive technologies to help people with disabilities. This involves the reattachment of the robot arm after repairing and updating with 3D printing and using modern hardware and software technology. We observed that the robotic arm has rotary and translation movements …

Chapman Ambassador Tour Robot, Alexandra Lewandowski, Yanni Parissis, Khiry Carter, Hilary Lee

Student Scholar Symposium Abstracts and Posters

Being a student ambassador improves a student's confidence and leadership skills. With an increasing demand for technology skills, our project will display how the ambassador robot can assist student ambassadors while improving upon their efficiency, by discussing information during college campus tours and familiarizing students with robot applications and their technology. The ambassador robot can support students during tours by answering a question about specific knowledge that may have slipped an ambassador's mind. The robot will also be able to create a group-focused atmosphere that will allow ambassadors to have the opportunity to lean on a dependable teammate for specific …

How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Can the rubber-hand illusion be extended to a moving robotic arm in different degrees of freedom (DOF), inducing sense of ownership & agency over the arm? We hypothesize that DOF closer to what humans possess will result in a stronger sense of ownership and agency.

Self-Driving Toy Car Using Deep Learning, Fahim Ahmed, Suleyman Turac, Mubtasem Ali

Publications and Research

Our research focuses on building a student affordable platform for scale model self-driving cars. The goal of this project is to explore current developments of Open Source hardware and software to build a low-cost platform consisting of the car chassis/framework, sensors, and software for the autopilot. Our research will allow other students with low budget to enter into the world of Deep Learning, self-driving cars, and autonomous cars racing competitions.

An Approach To Fast Multi-Robot Exploration In Buildings With Inaccessible Spaces, Matt Mcneill, Damian Lyons

Faculty Publications

The rapid exploration of unknown environments is a common application of autonomous multi-robot teams. For some types of exploration missions, a mission designer may possess some rudimentary knowledge about the area to be explored. For example, the dimensions of a building may be known, but not its floor layout or the location of furniture and equipment inside. For this type of mission, the Space- Based Potential Field (SBPF) method is an approach to multirobot exploration which leverages a priori knowledge of area bounds to determine robot motion. Explored areas and obstacles exert a repulsive force, and unexplored areas exert an …

Reasoning From Point Clouds, Joey Wilson

Computer Engineering

Over the past two years, 3D object detection has been a major area of focus across industry and academia. This is primarily due to the difficulty of learning data from point clouds. While camera images are fixed size and can therefore be easily trained on using convolution, point clouds are unstructured series of points in three dimensions. Therefore, there is no fixed number of features, or a structure to run convolution on. Instead, researchers have developed many ways of attempting to learn from this data, however there is no clear consensus on what is the best method, as each has …

Mobile Robot Platform, Sukhman S. Marok

Electrical Engineering

The Mobile Robot Platform is a research and development tool designed for researchers working in the field of robotics. The cost of existing mobile robot platforms can easily be in the thousands of dollars, leading many researchers to choose between spending the time to create their own platform or buying an expensive pre-existing solution. The Mobile Robot Platform proposed combines pre-existing open source software and hardware solutions, along with a strong mechanical base that is capable of navigating on flat surfaces. The robot is designed to have many of the necessary components needed for teleoperation as well as autonomous navigation. …

Involuntary Signal-Based Grounding Of Civilian Unmanned Aerial Systems (Uas) In Civilian Airspace, Keith Conley

Master's Theses

This thesis investigates the involuntary signal-based grounding of civilian unmanned aerial systems (UAS) in unauthorized air spaces. The technique proposed here will forcibly land unauthorized UAS in a given area in such a way that the UAS will not be harmed, and the pilot cannot stop the landing. The technique will not involuntarily ground authorized drones which will be determined prior to the landing. Unauthorized airspaces include military bases, university campuses, areas affected by a natural disaster, and stadiums for public events. This thesis proposes an early prototype of a hardware-based signal based involuntary grounding technique to handle the problem …

Robot Simulation Analysis, Jacob Miller, Jeremy Evert

Student Research

• Simulate virtual robot for test and analysis

• Analyze SLAM solutions using ROS

• Assemble a functional Turtlebot

• Emphasize projects related to current research trajectories for NASA, and general robotics applications

A Co-Optimal Coverage Path Planning Method For Aerial Scanning Of Complex Structures, Zhexiong Shang, Justin Bradley, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

The utilization of unmanned aerial vehicles (UAVs) in survey and inspection of civil infrastructure has been growing rapidly. However, computationally efficient solvers that find optimal flight paths while ensuring high-quality data acquisition of the complete 3D structure remains a difficult problem. Existing solvers typically prioritize efficient flight paths, or coverage, or reducing computational complexity of the algorithm – but these objectives are not co-optimized holistically. In this work we introduce a co-optimal coverage path planning (CCPP) method that simultaneously co-optimizes the UAV path, the quality of the captured images, and reducing computational complexity of the solver all while adhering to …

A Comparison Of Contextual Bandit Approaches To Human-In-The-Loop Robot Task Completion With Infrequent Feedback, Matt Mcneill, Damian Lyons

Faculty Publications

Artificially intelligent assistive agents are playing an increased role in our work and homes. In contrast with currently predominant conversational agents, whose intelligence derives from dialogue trees and external modules, a fully autonomous domestic or workplace robot must carry out more complex reasoning. Such a robot must make good decisions as soon as possible, learn from experience, respond to feedback, and rely on feedback only as much as necessary. In this research, we narrow the focus of a hypothetical robot assistant to a room tidying task in a simulated domestic environment. Given an item, the robot chooses where to put …

A Deep Learning Approach For Motion Segment Estimation For Pipe Leak Detection Robot, Cihan Uyanik, Erdem Erdemir, Erkan Kaplanoglu, Ali Sekmen

Computer Science Faculty Research

The trajectory motion of a robot can be a valuable information to estimate the localization of an autonomous robotic system, especially in a very dynamic but structurally-known environments like water pipes where the sensor readings are not reliable. The main focus of this research is to estimate the location of meso-scale robots using a deep-learning-based motion trajectory segment detection system from recorded sensory measurements while the robot travels through a pipe system. The idea is based on the classification of the motion measurements, acquired by inertial measurement unit (IMU), by exploiting the deep learning approach. Proposed idea and utilized methodology …

A Novel Gripping System For Corrugated Box Grasping And Manipulation For Unmanned Aerial Vehicles, Trigun Maroo

Theses and Dissertations

An Unmanned Aerial Vehicle (UAV) can carry packages to locations that are unreachable by an autonomous ground vehicle (AGV) using a suitable gripper system. A novel gripping system for grasping corrugated boxes which has the potential to be mounted on a UAV is presented. The proposed gripping system uses two pairs of perpendicularly mounted linear actuators to move the end effectors, geared such that they are operated with a single control input. The mechanism is designed to handle position and orientation errors of the target object automatically in the specified grasping zone without the need of a control system. The …

Distributed Spatiotemporal Control And Dynamic Information Fusion For Multiagent Systems, Dzung Minh Duc Tran

USF Tampa Graduate Theses and Dissertations

The first objective of this dissertation is to develop novel distributed control architectures allowing spatiotemporal control of multiagent systems as applied to formation control. In addition, its second objective is to introduce distributed estimation frameworks for dynamic information fusion for addressing the heterogeneity in sensor networks.

Changing the spatial and temporal properties of agent teams in a distributed manner and in real-time is an open problem in the control system literature as multiagent systems are often required to complete tasks with ever-increasing complexity in adverse conditions and dynamic environments. Motivated by this standpoint, this dissertation aims to address challenges related …

Communication Capability For A Simulation-Based Test And Evaluation Framework For Autonomous Systems, Ntiana Sakioti

Computational Modeling & Simulation Engineering Theses & Dissertations

The design and testing process for collaborative autonomous systems can be extremely complex and time-consuming, so it is advantageous to begin testing early in the design. A Test & Evaluation (T&E) Framework was previously developed to enable the testing of autonomous software at various levels of mixed reality. The Framework assumes a modular approach to autonomous software development, which introduces the possibility that components are not in the same stage of development. The T&E Framework allows testing to begin early in a simulated environment, with the autonomous software methodically migrating from virtual to augmented to physical environments as component development …

Audio Beat Detection With Application To Robot Drumming, Michael James Engstrom

Dissertations and Theses

This Drumming Robot thesis demonstrates the design of a robot which can play drums in rhythm to an external audio source. The audio source can be either a pre-recorded .wav file or a live sample .wav file from a microphone. The dominant beats-per-minute (BPM) of the audio would be extracted and the robot would drum in time to the BPM. A Fourier Analysis-based BPM detection algorithm, developed by Eric Scheirer (Tempo and beat analysis of acoustical musical signals)ⁱ was adopted and implemented. In contrast to other popular algorithms, the main advantage of Scheirer's algorithm is it has …

Exercises Integrating High School Mathematics With Robot Motion Planning, Ronald I. Greenberg, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

This paper presents progress in developing exercises for high school students incorporating level-appropriate mathematics into robotics activities. We assume mathematical foundations ranging from algebra to precalculus, whereas most prior work on integrating mathematics into robotics uses only very elementary mathematical reasoning or, at the other extreme, is comprised of technical papers or books using calculus and other advanced mathematics. The exercises suggested are relevant to any differerential-drive robot, which is an appropriate model for many different varieties of educational robots. They guide students towards comparing a variety of natural navigational strategies making use of typical movement primitives. The exercises align …

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 …

A Low-Cost Soft Robotic Hand Exoskeleton For Use In Therapy Of Limited Hand–Motor Function, Grant Rudd, Liam Daly, Vukica Jovanovic, Filip Cukov

Engineering Technology Faculty Publications

We present the design and validation of a low-cost, customizable and 3D-printed anthropomorphic soft robotic hand exoskeleton for rehabilitation of hand injuries using remotely administered physical therapy regimens. The design builds upon previous work done on cable actuated exoskeleton designs by implementing the same kinematic functionality, but with the focus shifted to ease of assembly and cost effectiveness as to allow patients and physicians to manufacture and assemble the hardware necessary to implement treatment. The exoskeleton was constructed solely from 3D-printed and widely available of-the-shelf components. Control of the actuators was realized using an Arduino microcontroller, with a custom-designed shield …

Utilizing Trajectory Optimization In The Training Of Neural Network Controllers, Nicholas Kimball

Master's Theses

Applying reinforcement learning to control systems enables the use of machine learning to develop elegant and efficient control laws. Coupled with the representational power of neural networks, reinforcement learning algorithms can learn complex policies that can be difficult to emulate using traditional control system design approaches. In this thesis, three different model-free reinforcement learning algorithms, including Monte Carlo Control, REINFORCE with baseline, and Guided Policy Search are compared in simulated, continuous action-space environments. The results show that the Guided Policy Search algorithm is able to learn a desired control policy much faster than the other algorithms. In the inverted pendulum …

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 …

Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore

School of Computing: Dissertations, Theses, and Student Research

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries.

To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We …

Design Of A Canine Inspired Quadruped Robot As A Platform For Synthetic Neural Network Control, Cody Warren Scharzenberger

Dissertations and Theses

Legged locomotion is a feat ubiquitous throughout the animal kingdom, but modern robots still fall far short of similar achievements. This paper presents the design of a canine-inspired quadruped robot named DoggyDeux as a platform for synthetic neural network (SNN) research that may be one avenue for robots to attain animal-like agility and adaptability. DoggyDeux features a fully 3D printed frame, 24 braided pneumatic actuators (BPAs) that drive four 3-DOF limbs in antagonistic extensor-flexor pairs, and an electrical system that allows it to respond to commands from a SNN comprised of central pattern generators (CPGs). Compared to the previous version …

An Efficient Multiple-Place Foraging Algorithm For Scalable Robot Swarms, Qi Lu

Computer Science ETDs

Searching and collecting multiple resources from large unmapped environments is an important challenge. It is particularly difficult given limited time, a large search area and incomplete data about the environment. This search task is an abstraction of many real-world applications such as search and rescue, hazardous material clean-up, and space exploration. The collective foraging behavior of robot swarms is an effective approach for this task. In our work, individual robots have limited sensing and communication range (like ants), but they are organized and work together to complete foraging tasks collectively. An efficient foraging algorithm coordinates robots to search and collect …

Mathematics And Programming Exercises For Educational Robot Navigation, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

This paper points students towards ideas they can use towards developing a convenient library for robot navigation, with examples based on Botball primitives, and points educators towards mathematics and programming exercises they can suggest to students, especially advanced high school students.

A Systematic Review Of Studies On Educational Robotics, Saira Anwar, Nicholas Alexander Bascou, Muhsin Menekse, Asefeh Kardgar

Journal of Pre-College Engineering Education Research (J-PEER)

There has been a steady increase in the number of studies investigating educational robotics and its impact on academic and social skills of young learners. Educational robots are used both in and out of school environments to enhance K–12 students’ interest, engagement, and academic achievement in various fields of STEM education. Some prior studies show evidence for the general benefits of educational robotics as being effective in providing impactful learning experiences. However, there appears to be a need to determine the specific benefits which have been achieved through robotics implementation in K–12 formal and informal learning settings. In this study, …

Evaluation Of Field Of View Width In Stereo-Vision-Based Visual Homing, Damian Lyons, Benjamin Barriage, Luca Del Signore

Faculty Publications

Visual homing is a local navigation technique used to direct a robot to a previously seen location by comparing the image of the original location with the current visual image. Prior work has shown that exploiting depth cues such as image scale or stereo-depth in homing leads to improved homing performance. While it is not unusual to use a panoramic field of view (FOV) camera in visual homing, it is unusual to have a panoramic FOV stereo-camera. So, while the availability of stereo-depth information may improve performance, the concomitant-restricted FOV may be a detriment to performance, unless specialized stereo hardware …

Chatbots: Conversation Killers Or Makers?, Jing Jiang

MITB Thought Leadership Series

Whether you’re aware of it or not, the chances are you’ve been chatting to robots of late. While these bots are faceless and unseen, don’t be fooled into thinking they aren’t there. In fact, chatbots, have been around since the 1960s at least, but with the progress in artificial intelligence, cloud computing and voice recognition, they’ve received both a functionality and a popularity boost. From the cosmetic to the life-changing, nowadays, chatbots can do anything from helping a person lose weight to assisting refugees applying for asylum.

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements, Miaomiao Wang

Western Research Forum

The development of reliable orientation, position and linear velocity estimation algorithms for the 3D visual-inertial navigation system (VINS) is instrumental in many applications, such as autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs). It is extremely important when the global position system (GPS) is not available in GPS-denied environments. Recently, observers design for VINS using landmark position measurements from Kinect sensors or stereo cameras has been increasingly investigated in the literature.

The aim of this work is to design a nonlinear observer for VINS under the assumption that landmark position measurements are intermittent. In practice, the landmark measurements are …