Robotics Commons^™

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

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

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 …

Design And Implementation Of Intuitive Human-Robot Teleoperation Interfaces, Lei Wu

USF Tampa Graduate Theses and Dissertations

We have designed and implemented a novel human-robot teleoperation interface based on an intuitive reference frame and hybrid inverse kinematics to perform activities of daily living(ADL) using multiple input devices.

Persons with disabilities often rely on caregivers or family members to assist in their daily living activities. Providing robotic assistants with easy and intuitive user interfaces to assist with ADL can improve their quality of life and lift some of the burdens on caregivers and family members. Current human-robot interface solutions, such as joysticks, Kinect based gesture recognition, and touchscreen-based solutions, including smartphones, are still far from being able to …

We Need Fuzzy Techniques To Design Successful Human-Like Robots, Vladik Kreinovich, Olga Kosheleva, Laxman Bokati

Departmental Technical Reports (CS)

In this chapter, we argue that to make sure that human-like robots exhibit human-like behavior, we need to use fuzzy techniques -- and we also provide details of this usage. The chapter is intended both for researchers and practitioners who are very familiar with fuzzy techniques and also for researchers and practitioners who do not know these techniques -- but who are interested in designing human-like robots.

Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values. In this work, we extend our previously-developed method for tuning networks of non-spiking neurons, the “Functional subnetwork approach” (FSA), to the tuning of networks composed of spiking neurons. This extension enables the direct assembly and tuning of networks of spiking neurons and synapses based on the network’s intended function, without the use of global optimization ormachine learning. To extend the FSA, we show that the dynamics of a generalized linear integrate and fire (GLIF) neuronmodel have fundamental similarities to those of …

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 …

Control Of A Human Arm Robotic Unit Using Augmented Reality And Optimized Kinematics, Carlo Canezo

USF Tampa Graduate Theses and Dissertations

There are more than 350000 amputees in the US who suffer loss of functionality in their daily living activities, and roughly 100000 of them are upper arm amputees. Many of these amputees use prostheses to compensate part of their lost arm function, including power prostheses. Research on 6-7 degree of freedom powered prostheses is still relatively new, and most commercially available powered prostheses are typically limited to 1 to 3 degrees of freedom. Due to the myriad of possible options for various powered protheses from different manufacturers, each configuration is governed by a distinct control scheme typically specific to the …

Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu

Publications

A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous …

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

Maseeh Summer Undergraduate Research Experience

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 …

Specially Designed Multi-Functional Search And Rescue Robot, Khabibullo Kh Nosirov, A.Sh. Shakhobiddinov, Mukhriddin Arabboev, Shohruh Begmatov, O.T. Togaev

Bulletin of TUIT: Management and Communication Technologies

In digital era, robots are becoming an integral part of human life due to their efficiency and high performance. In recent years, search and rescue robot systems are used tremendously in a natural disaster. Nowadays, many areas of the world are getting affected due to natural disasters. Disasters can be exceptional and unstoppable events that are either man-made or natural, such as building collapse, earthquakes, wildfires, and floods, etc. This witnesses the importance of search and rescue robot systems in the emergency field. In the emergency field, a variety of sensing and wireless technologies are used in remote and vision …

Evaluating The Potential Of Drone Swarms In Nonverbal Hri Communication, Kasper Grispino, Damian Lyons, Truong-Huy Nguyen

Faculty Publications

Human-to-human communications are enriched with affects and emotions, conveyed, and perceived through both verbal and nonverbal communication. It is our thesis that drone swarms can be used to communicate information enriched with effects via nonverbal channels: guiding, generally interacting with, or warning a human audience via their pattern of motions or behavior. And furthermore that this approach has unique advantages such as flexibility and mobility over other forms of user interface. In this paper, we present a user study to understand how human participants perceived and interpreted swarm behaviors of micro-drone Crazyflie quadcopters flying three different flight formations to bridge …

The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Using episodes from the show Black Mirror as a study tool - a show that features tales that explore techno-paranoia - the course analyzes legal and policy considerations of futuristic or hypothetical case studies. The case studies tap into the collective unease about the modern world and bring up a variety of fascinating key philosophical, legal, and economic-based questions.

Tech Policy And Legal Theory Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Technology has changed dramatically over the last couple of decades. Currently, virtually all business industries are powered by large quantities of data. The potential as well as actual uses of business data, which oftentimes includes personal user data, raise complex issues of informed consent and data protection. This course will explore many of these complex issues, with the goal of guiding students into thinking about tech policy from a broad ethical perspective as well as preparing students to responsibly conduct themselves in different areas and industries in a world growingly dominated by technology.

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is …

Cooperative Target Tracking In Balanced Circular And Elliptical Formations, Lili Ma, Naira Hovakimyan

Publications and Research

This paper extends our earlier results on cooperative target tracking in cyclic pursuit using a group of mobile robots by further prescribing the formation radius and achieving an elliptical formation pattern. Prescribing the formation radius of a balanced circular formation is achieved by adjusting a parameter in the existing control input to each robot. The new elliptical formation pattern is obtained via a transformation matrix. Both single-integrator and double-integrator robot models are considered. The effectiveness of the proposed schemes is demonstrated by simulation examples.

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 …

Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner

Publications and Research

Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself …

Human Supremacy As Posthuman Risk, Daniel Estrada

The Journal of Sociotechnical Critique

Human supremacy is the widely held view that human interests ought to be privileged over other interests as a matter of ethics and public policy. Posthumanism is the historical situation characterized by a critical reevaluation of anthropocentrist theory and practice. This paper draws on animal studies, critical posthumanism, and the critique of ideal theory in Charles Mills and Serene Khader to address the appeal to human supremacist rhetoric in AI ethics and policy discussions, particularly in the work of Joanna Bryson. This analysis identifies a specific risk posed by human supremacist policy in a posthuman context, namely the classification of …

Artificial Intelligence Towards Future Industrial Opportunities And Challenges, Gizealew Dagnaw

African Conference on Information Systems and Technology

The industry 4.0 will bring reflective changes to our society, including an important digital shift in the manufacturing sector. At present, several manufacturing firms are trying to adopt the practices of industry 4.0 throughout their supply chain. The Fourth Industrial Revolution and the artificial intelligence at its core are fundamentally changing the way we live, work and interact as citizens. The complexity of this transformation may look overwhelming and to many threatening. Recently, the dramatic growth of new generation information technologies has prompted several countries to seek new strategies for industrial revolution. The globalization and the competitiveness are forcing companies …