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2020

Robotics

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Full-Text Articles in Engineering

Human-Robot Interaction For Assistive Robotics, Jiawei Li Dec 2020

Human-Robot Interaction For Assistive Robotics, Jiawei Li

Dissertations

This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and …


Reinforcement Learning Approach For Inspect/Correct Tasks, Hoda Nasereddin Dec 2020

Reinforcement Learning Approach For Inspect/Correct Tasks, Hoda Nasereddin

LSU Doctoral Dissertations

In this research, we focus on the application of reinforcement learning (RL) in automated agent tasks involving considerable target variability (i.e., characterized by stochastic distributions); in particular, learning of inspect/correct tasks. Examples include automated identification & correction of rivet failures in airplane maintenance procedures, and automated cleaning of surgical instruments in a hospital sterilization processing department. The location of defects and the corrective action to be taken for each varies from task episode. What needs to be learned are optimal stochastic strategies rather than optimization of any one single defect type and location. RL has been widely applied in robotics …


Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki Dec 2020

Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki

Mechanical Engineering Undergraduate Honors Theses

Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the great achievements of deep reinforcement learning in various domains including finance,medicine, healthcare, video games, robotics and computer vision.Deep neural network was started with multi-layer perceptron (1stgeneration) and developed to deep neural networks (2ndgeneration)and it is moving forward to spiking neural networks which are knownas3rdgeneration of neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically-realistic models of neurons to carry out computation. In this thesis, we first provide a comprehensive review …


Emergency Landing And Guidance System, Joseph Alarid Dec 2020

Emergency Landing And Guidance System, Joseph Alarid

Master's Theses

Every year there are thousands of aviation accidents along with hundreds of human deaths that happen around the world. While the data is sparse, it is well documented that many of these happen from emergency landings gone awry. While pilots can generally make great landings in clear daytime conditions, they are significantly handicapped when it comes to landing at night or amongst poor visibility conditions.

Due to the nature of this problem and some of the large scale advances in software technology we propose a solution that provides a significant improvement from the status quo. Using transfer learning on neural …


Roboat - Rescue Operations Bot Operating In All Terrains, Akshay Gulhane Oct 2020

Roboat - Rescue Operations Bot Operating In All Terrains, Akshay Gulhane

USF Tampa Graduate Theses and Dissertations

Natural calamities are on a rise with each passing year. Disasters like floods and fire take many lives all around the world, especially in remote areas or less developed countries. One such incident was the Kerala Floods in India where rescue services had difficulty reaching to all the people on time since a huge landmass (more than 9 districts) was flooded and hence villagers or other people risked their lives to save others in danger without proper safety equipment. Amazon Rainforest Fires was another example for a major destruction of an ecosystem. The main reason for lack of facilities in …


Interfaces Expanding Boundaries Of Architectural Design Education Withindustrial Robots, Marwan Halabi Oct 2020

Interfaces Expanding Boundaries Of Architectural Design Education Withindustrial Robots, Marwan Halabi

Architecture and Planning Journal (APJ)

Throughout an extensive period of time, advanced mechanical tools such as robotic arms have been a common prospect in many production industries. Today, and as the potentials in digital design and fabrication technologies are seen to enhance complex tridimensional construction processes, robots are rapidly being integrated within the architectural education curriculum. In a relatively short amount of time, many architectural faculties around the globe have set up experimental digital fabrication laboratories with 3D printers, CNC machines, and robotic arms. This paper will argue the use of robots in education beyond the opportunities provided by the already traditional automated modes of …


Autonomous Drone-Based Sensor Package Deployment To The Underside Of Structures, Sabrina Rose Carroll Oct 2020

Autonomous Drone-Based Sensor Package Deployment To The Underside Of Structures, Sabrina Rose Carroll

Theses and Dissertations

The objective of this project is to design, develop and experimentally test an Unmanned Aircraft System (UAS, commonly known as a drone) for the deployment of sensor packages to the underside of structures. This work begins with an in-depth review of existing automation techniques for various drone applications focusing on applications requiring interaction with the environment. Further reviewed is the impact of structures above the UAS during flight on the behavior of the aircraft.

Considering these topics, the development of a custom drone is presented to address the difficulties of delivering a package to the underside of a structure. Starting …


3d-Printed Leg Design And Modification For Improved Support On A Quadruped Robot, Jasmin S. Collins Sep 2020

3d-Printed Leg Design And Modification For Improved Support On A Quadruped Robot, Jasmin S. Collins

Undergraduate Research & Mentoring Program

The Agile and Adaptive Robotics Lab aims to uncover the biological and physiological complexities in animal agility and adaptive control, which can be replicated through robotics and provide further applications in biology and medicine. One project within the lab focuses on understanding structure, actuation, and control through the modeling of a canine quadruped robot.

The AARL has developed a full-body quadruped robot with artificial muscles that control limb movement and a body that is built from 3D-printed parts. This specific project involved modification of these existing parts to (a) minimize deflections in the front legs, causing unwanted lateral and abduction/adduction …


Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi Jul 2020

Synthesizing Expressive Behaviors For Humanoid Robots, Mathias Irwan Sunardi

Dissertations and Theses

Humanoid robots are expected to be able to communicate with expressive gestures at the same level of proficiency as humans. However, creating expressive gestures for humanoid robots is difficult and time consuming due to the high number of degrees of freedom (DOF) and the iterations needed to get the desired expressiveness.

Current robot motion editing software has varying levels of sophistication of motion editing tools ranging from basic ones that are text-only, to ones that provide graphical user interfaces (GUIs) which incorporate advanced features, such as curve editors and inverse kinematics. These tools enable users to create simple motions; but …


Flexible Fault Tolerance For The Robot Operating System, Sukhman S. Marok Jun 2020

Flexible Fault Tolerance For The Robot Operating System, Sukhman S. Marok

Master's Theses

The introduction of autonomous vehicles has the potential to reduce the number of accidents and save countless lives. These benefits can only be realized if autonomous vehicles can prove to be safer than human drivers. There is a large amount of active research around developing robust algorithms for all parts of the autonomous vehicle stack including sensing, localization, mapping, perception, prediction, planning, and control. Additionally, some of these research projects have involved the use of the Robot Operating System (ROS). However, another key aspect of realizing an autonomous vehicle is a fault-tolerant design that can ensure the safe operation of …


Non-Obstetrical Robotic-Assisted Laparoscopic Surgery In Pregnancy: A Systematic Literature Review., Courtney Capella, Joseph Godovchik, Thenappan Chandrasekar, Huda B. Al-Kouatly May 2020

Non-Obstetrical Robotic-Assisted Laparoscopic Surgery In Pregnancy: A Systematic Literature Review., Courtney Capella, Joseph Godovchik, Thenappan Chandrasekar, Huda B. Al-Kouatly

Department of Urology Faculty Papers

Urologic and gynecologic surgeons are the top utilizers of robotic surgery; however, non-obstetrical robotic-assisted laparoscopic surgery (RALS) in pregnant patients is infrequent. A systematic literature review was performed to ascertain the frequency, indication and complications of RALS in pregnancy. Results showed thirty-eight pregnancies from eleven publications between 2008-2020. Five cases were for urologic indication and thirty-three for gynecologic indication. Minimal surgical alterations were required. Although no adverse maternal-fetal outcomes were reported, there are not enough cases published to determine safety. This review demonstrates the feasibility of RALS for the pregnant population in the hands of competent robotic surgeons.


Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra May 2020

Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra

Faculty Publications

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility …


Using Robotics And Engineering Design Inquiries To Optimize Learning For Middle Level Teachers: A Case Study, Iman Chafik Chahine, Norman Robinson Iii, Kimbeni Mansion May 2020

Using Robotics And Engineering Design Inquiries To Optimize Learning For Middle Level Teachers: A Case Study, Iman Chafik Chahine, Norman Robinson Iii, Kimbeni Mansion

Publications & Research

This exploratory case study reports findings on 20 middle-level science and mathematics teachers’ perceptions of the effectiveness of a one-year project in which teachers engaged in using robotics and engineering design inquiries in their classrooms. Principled by Bandura’s Social Learning Theory (SLT) and using mixed methods approaches, the study measured teachers' efficacy through the Mathematics Teaching Efficacy Belief Instrument (MTEBI) and observation logs before and after the program. The results of this study showed statistically significant differences between PRE MTEBI and POST MTEBI scores. Furthermore, five themes emerged that illuminated potential affordances and constraints that teachers perceive as opportunities and …


Drone Proximity Detection Via Air Disturbance Analysis, Qian Zhao, Jason Hughes Apr 2020

Drone Proximity Detection Via Air Disturbance Analysis, Qian Zhao, Jason Hughes

Faculty Publications

The use of unmanned aerial vehicles (drones) is expanding to commercial, scientific, and agriculture applications, including surveillance, product deliveries and aerial photography. One challenge for applications of drones is detecting obstacles and avoiding collisions. A typical solution to this issue is the use of camera sensors or ultrasonic sensors for obstacle detection or sometimes just manual control (teleoperation). However, these solutions have costs in battery lifetime, payload, operator skill. We note that there will be an air disturbance in the vicinity of the drone when it’s moving close to obstacles or other drones. Our objective is to detect obstacles from …


Design, Assessment, And Comparison Of Antagonistic, Cable-Driven, Variable Stiffness Actuators, Ryan P. Moore Apr 2020

Design, Assessment, And Comparison Of Antagonistic, Cable-Driven, Variable Stiffness Actuators, Ryan P. Moore

Master's Theses (2009 -)

This thesis presents the designs and test results for two antagonistic, cable-driven, variable stiffness actuator designs. Each of these variable stiffness actuators is compact, has a large range of controllable stiffness, and limits the inertia at the robotic link it is controlling. Each design consists of a cable running through a set of three pulleys. Tension on the cable displaces a linear spring, which moves along a path designed to achieve quadratic spring behavior. One design uses a variable radius path to achieve the nonlinear elastic behavior while the other uses a fixed radius (lever) path.A quasi-static model of …


Advanced Mechatronics, Hao Su Apr 2020

Advanced Mechatronics, Hao Su

Open Educational Resources

Project-based course on the design of mechatronic devices to address needs identified by hospital-based clinicians and industry. Students work in teams to develop a mechatronic prototype. The lectures will cover the design of medical devices and robotics including sensors, actuators, and robots. The students will communicate with customers to understand design needs, then conduct study on prior art, intellectual property, due diligence, and idea conceptualization. Students will present ideas in class and to a broad audience from local industry. Students will also write a publication-quality final report, which they will be encouraged for publication submission.


Engineering Design I, Hao Su Apr 2020

Engineering Design I, Hao Su

Open Educational Resources

Introduction to robotics


Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le Mar 2020

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 …


Me And My Robot Smiled At One Another: The Process Of Socially Enacted Communicative Affordance In Human-Machine Communication, Carmina Rodríguez-Hidalgo Feb 2020

Me And My Robot Smiled At One Another: The Process Of Socially Enacted Communicative Affordance In Human-Machine Communication, Carmina Rodríguez-Hidalgo

Human-Machine Communication

The term affordance has been inconsistently applied both in robotics and communication. While the robotics perspective is mostly object-based, the communication science view is commonly user-based. In an attempt to bring the two perspectives together, this theoretical paper argues that social robots present new social communicative affordances emerging from a two-way relational process. I first explicate conceptual approaches of affordance in robotics and communication. Second, a model of enacted communicative affordance in the context of Human-Machine Communication (HMC) is presented. Third and last, I explain how a pivotal social robot characteristic—embodiment—plays a key role in the process of social communicative …


Autonomous Control Of A Line Follower Robot Using A Q-Learning Controller, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi, Donald C. Wunsch Jan 2020

Autonomous Control Of A Line Follower Robot Using A Q-Learning Controller, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a MIMO simulated annealing (SA)-based Q-learning method is proposed to control a line follower robot. The conventional controller for these types of robots is the proportional (P) controller. Considering the unknown mechanical characteristics of the robot and uncertainties such as friction and slippery surfaces, system modeling and controller designing can be extremely challenging. The mathematical modeling for the robot is presented in this paper, and a simulator is designed based on this model. The basic Q-learning methods are based pure exploitation and the ε -greedy methods, which help exploration, can harm the controller performance after learning completion …


Deployment Of Deep Reinforcement Learning Algorithms On Physical Robotic Systems, P. Surya . Jan 2020

Deployment Of Deep Reinforcement Learning Algorithms On Physical Robotic Systems, P. Surya .

Manipal Institute of Technology, Manipal Theses and Dissertations

In the recent years, Reinforcement Learning (RL), has surfaced as an impressive tool for solving complex sequential decision-making problems in control theory. Its major grasp on control theory has been on Markov decision problems (MDP) and its variants. It overcomes the long observed problems of the curse of dimensionality and the curse of modeling. This outperforms the classical Dynamic Programming (DP) that falter under these curses. The work is to use this advantage in our favour to leverage autonomous navigation in a model learnable environment or otherwise. The work involves the use of a Meta OS called Robot Operating System …


Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor Jan 2020

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. …


A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal Jan 2020

A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal

Theses and Dissertations--Electrical and Computer Engineering

Advances in computing power in recent years have facilitated developments in autonomous robotic systems. These robotic systems can be used in prosthetic limbs, wearhouse packaging and sorting, assembly line production, as well as many other applications. Designing these autonomous systems typically requires robotic system and world models (for classical control based strategies) or time consuming and computationally expensive training (for learning based strategies). Often these requirements are difficult to fulfill. There are ways to combine classical control and learning based strategies that can mitigate both requirements. One of these ways is to use a gravity compensated torque control with reinforcement …


Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch Jan 2020

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 …


A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan Jan 2020

A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan

Open Access Theses & Dissertations

Soft robotics is a growing field in robotics research. Heavily inspired by biological systems, these robots are made of softer, non-linear, materials such as elastomers and are actuated using several novel methods, from fluidic actuation channels to shape changing materials such as electro-active polymers. Highly non-linear materials make modeling difficult, and sensors are still an area of active research. These issues have rendered typical control and modeling techniques often inadequate for soft robotics. Reinforcement learning is a branch of machine learning that focuses on model-less control by mapping states to actions that maximize a specific reward signal. Reinforcement learning has …


Quickcut Cnc Waterjet Cutter, Kelly V. Robbins Jan 2020

Quickcut Cnc Waterjet Cutter, Kelly V. Robbins

Williams Honors College, Honors Research Projects

This design project was dedicated to improving the existing design and making functional the QuickCut CNC Waterjet Cutter. The scope of work consisted of making the machine mobile and more structurally stable as well as programming the CNC controls. The project was started in the 2018/19 school year by a former mechanical engineering student. The subsystems consist of the frame, power, motor, water pump and associated plumbing, nozzle, abrasive feed system, x/y gantry, Arduino control system and the cutting bed. Unfortunately, due to the COVID-19 pandemic, the full scope was not able to be completed in its entirety.