This work presents two approaches for integrating data from a low cost GPS receiver in a Monte Carlo localization algorithm. Firstly, an easily applicable method based on data in the standard NMEA protocol is shown. Secondly, an original algorithm utilizing lower level pseudorange measurements accessed in binary receiver-specific format is presented. In addition, a set of tools for analysis of GPS measurement errors on receivers with SiRF III chipset was implemented

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Hoy día, las sociedades se sirven de los avances de la tecnología para suplir al hombre en la realización de tareas tediosas o pesadas, lo que ha dado lugar al desarrollo de la robótica y la automatización. El uso de los robots industriales ha crecido vertiginosamente en muchas industrias manufactureras desde los años 70s y 80s, en especial en la automotriz donde la mayoría son usados en tareas de soldadura de arco y por puntos. La Federación Internacional de Robótica (IFR) estima que la población mundial de robots industriales en funcionamiento, aumentará de 1 millón de unidades a 1.38 millones a finales del 2014, lo que representa una tasa media de crecimiento anual de menos del 6% entre 2012 y 2014.

Ce projet de recherche, intitulé Téléopération d'un robot collaboratif par outil haptique traite un des problèmes contemporains de la robotique, à savoir la coopération entre l'humain et la machine. La robotique est en pleine expansion depuis maintenant deux décennies: les robots investissent de plus en plus l'industrie, les services ou encore l'assistance à la personne et se diversifient considérablement. Ces nouvelles tendances font sortir les robots des cages dans lesquelles ils étaient placés et ouvrent grand la porte vers de nouvelles applications. Parmi elles, la coopération et les interactions avec l'humain représentent une réelle opportunité pour soulager l'homme dans des tâches complexes, fastidieuses et répétitives. En parallèle de cela, la robotique moderne s'oriente vers un développement massif du domaine humanoïde. Effectivement, plusieurs expériences sociales ont montré que l'être humain, constamment en interaction avec les systèmes qui l'entourent, a plus de facilités à contribuer à la réalisation d'une tâche avec un robot d'apparence humaine plutôt qu'avec une machine. Le travail présenté dans ce projet de recherche s'intègre dans un contexte d'interaction homme-robot (IHR) qui repose sur la robotique humanoïde. Le système qui en découle doit permettre à un utilisateur d'interagir efficacement et de façon intuitive avec la machine, tout en respectant certains critères, notamment de sécurité. Par une mise en commun des compétences respectives de l'homme et du robot humanoïde, les interactions sont améliorées. En effet, le robot peut réaliser une grande quantité d'actions avec précision et sans se fatiguer, mais n'est pas nécessairement doté d'une prise de décision adaptée à la situation, contrairement à l'homme qui est capable d'ajuster son comportement naturellement ou en fonction de son expérience. En d'autres termes, ce système cherche à intégrer le savoir-faire et la capacité de réflexion humaine avec la robustesse, l'efficacité et la précision du robot. Dans le domaine de la robotique, le terme d'interaction intègre également la notion de contrôle. La grande majorité des robots reçoit des commandes machines qui sont généralement des consignes de trajectoire, qu'ils sont capables d'interpréter. Or, plusieurs interfaces de contrôle sont envisageables, notamment celles utilisant des outils haptiques, qui permettent à un utilisateur d'avoir un ressenti et une perception tactile. Ces outils comme tous ceux qui augmentent le degré de contrôle auprès de l'utilisateur, en ajoutant un volet sensoriel, sont parfaitement adaptés pour ce genre d'applications. Dans ce projet, deux outils haptiques sont assemblés puis intégrés à une interface de contrôle haptique dans le but de commander le bras d'un robot humanoïde. Ainsi, l'homme est capable de diriger le robot tout en ajustant ses commandes en fonction des informations en provenance des différents capteurs du robot, qui lui sont retranscrites visuellement ou sensoriellement.

Les robots humanoïdes sont les plus appropriés pour travailler en coopération avec l'homme. En effet, puisque les humains sont naturellement habitués à collaborer entre eux, un robot avec des capacités sensorielles et de locomotion semblables aux leurs, sera le plus adapté. Cette thèse vise à rendre les robot humanoïdes capables d'aider l'homme, afin de concevoir des 'humanoïdes collaboratifs'. On considère ici la tâche de transport collaboratif d'objets. D'abord, on montre comment l'utilisation simultanée de vision et de données haptiques peut améliorer la collaboration. Une stratégie combinant asservissement visuel et commande en admittance est proposée, puis validée dans un scénario de transport collaboratif homme/humanoïde.Ensuite, on présente un algorithme de génération de marche, prenant intrinsèquement en compte la collaboration physique. Cet algorithme peut être spécifié suivant que le robot guide (leader) ou soit guidé (follower) lors de la tâche. Enfin, on montre comment le transport collaboratif d'objets peut être réalisé dans le cadre d'un schéma de commande optimale pour le corps complet. / Humanoid robots provide many advantages when working together with humans to perform various tasks. Since humans in general have alot of experience in physically collaborating with each other, a humanoid with a similar range of motion and sensing has the potential to do the same.This thesis is focused on enabling humanoids that can do such tasks together withhumans: collaborative humanoids. In particular, we use the example where a humanoid and a human collaboratively carry and transport objectstogether. However, there is much to be done in order to achieve this. Here, we first focus on utilizing vision and haptic information together forenabling better collaboration. More specifically the use of vision-based control together with admittance control is tested as a framework forenabling the humanoid to better collaborate by having its own notion of the task. Next, we detail how walking pattern generators can be designedtaking into account physical collaboration. For this, we create leader and follower type walking pattern generators. Finally,the task of collaboratively carrying an object together with a human is broken down and implemented within an optimization-based whole-bodycontrol framework.

This thesis aims at real-time measurements of human trust, satisfaction, and frustration in human-robot teaming. Recent studies suggest that humans are inclined to have a negative attitude towards using autonomous systems. These ndings elevate the necessity of conducting research to better understand the key factors that a ect the levels of trust, satisfaction and frustration in Human-Robot Interaction (HRI). We utilized a new sequential and collaborative approach for HRI data collection that employed trust, satisfaction and frustration as primarily evaluative metrics. We also used haptic feedback through a soft actuator armband to help our human subjects control a robotic hand for grabbing or not grabbing an object during our interaction scenarios. Three experimental studies were conducted during our research of which the rst was related to the evaluation of aforementioned metrics through a collabora- tive approach between the Baxter robot and human subjects. The second experiment embodied the evaluation of a newly fabricated 3D- nger for the I-Limb robotic hand through a nuclear-waste glove. The third experiment was based on the two previous studies that focused on real-time measurements of trust, satisfaction and frustration in human-robot teaming with the addition of pressure feedback to the system through soft actuators. In the last case, human subjects had more controls over our robotic systems compared to earlier experiments leading to a more collaborative interaction and teaming. The results of these experiments illustrated that human subjects can rebuild their trust and also increase their satisfaction levels while lowering their frus- tration levels after failures or any faulty behavior. Furthermore, our analyses showed that our methods are highly e ective for collecting honest and genuine data from hu- man subjects and lays the foundation for more-involved future research in the domain of human-robot teaming. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

by Lam Miu-Ling. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 64-67). / Abstracts in English and Chinese. / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Mathematical Preliminaries and Problem Definition --- p.6 / Chapter 2.1 --- Grasp Synthesis in Discrete Domain / Chapter 2.2 --- Assumptions / Chapter 2.3 --- Frictionless Form-Closure Grasp / Chapter 2.4 --- Frictional Form-Closure Grasp / Chapter 2.5 --- Problem Definition / Chapter Chapter 3. --- A Qualitative Test Algorithm and a Local Search Algorithm --- p.18 / Chapter 3.1 --- A Qualitative Test Algorithm / Chapter 3.2 --- A Local Search Algorithm / Chapter 3.3 --- Grasp Planning under Kinematic Constraints / Chapter Chapter 4. --- A Divide-and-Conquer Technique --- p.29 / Chapter 4.1. --- Determining a Separating Hyperplane / Chapter 4.2. --- Divide-and-Conquer in Frictionless Case / Chapter 4.3. --- Divide-and-Conquer in Frictional Case / Chapter Chapter 5. --- Implementation and Examples --- p.40 / Chapter 6.1. --- Examples of Frictionless Grasps / Chapter 6.2. --- Examples of Frictional Grasps / Chapter 6.3. --- Examples of Grasps under Kinematic Constraints / Chapter Chapter 6. --- Conclusions --- p.62 / Bibliography --- p.64

Teleoperated robotic surgical systems such as daVinci are widely used for laparoscopic surgeries. The currently available daVinci system does not provide haptic feedback. Prior research has shown that the addition of haptic feedback improves surgeons' performance during minimally invasive surgeries. Other authors have implemented haptic feedback in the daVinci robot, but some issues made them impractical for clinical use. In this work, two strain gauge force-sensing devices were created for the patient side manipulator of the daVinci surgical robot. These devices were designed to be easily added to the existing system and used for the real-time force feedback in the daVinci robot. The proposed system has high sensitivity and resolution, matches the required force measurement range, and has high signal-to-noise ratio, which implies high signal quality. However, the absolute errors of the currently built devices are high due to the manufacturing techniques used on the prototype that could be improved upon for a deployed device. This work demonstrates fast 3-DOF force measurements on the daVinci robot without any robot or instrument modifications. While the present system has significant systematic errors, these can be mitigated by altering the mechanical design to improve the accuracy of the system.

"When treating highly-infectious diseases such as Ebola, health workers are at high risk of infection during the doffing of Personal Protective Equipment (PPE). This is due to factors such as fatigue, hastiness, and inconsistency in training. The introduction of a semi-autonomous robot doffing assistant has the potential to increase the safety of the doffing procedure by assisting the human during high-risk sub-tasks. The addition of a robot into the procedure introduces the need to transform a purely human task into a sequence of safe and effective human-robot collaborative actions. We take advantage of the fact that the human can do the more intricate motions during the procedure. Since diseases like Ebola can spread through the mucous membranes of the eyes, ears, nose, and mouth our goal is to keep the human’s hands away from his or her face as much as possible. Thus our framework focuses on using the robot to help avoid such human risky motion. As secondary goals, we seek to also minimize the human’s effort and make the robot’s motion intuitive for the human. To address different versions and variants of PPE, we propose a way of segmenting the doffing procedure into a sequence of human and robot actions such that the robot only assists when necessary. Our framework then synthesizes assistive motions for the robot that perform parts of the tasks according to the metrics above. Our experiments on five doffing tasks suggest that the introduction of a robot assistant improves the safety of the procedure in three out of four of the high-risk doffing tasks while reducing effort in all five tasks."

Fitness is important to achieve day to day tasks in our lives. It is significantly more important for the elderly as the functionality of the body declines. Fullerton Fitness Test (FFT) is a set of exercises to assess the fitness of the elderly. It was developed at Fullerton University by Dr. Roberta Rikli and Dr. Jessie Jones as a part of the LifeSpan Wellness Program. Under FFT, an individual is asked to go through a certain range of motions and based on these motions, a physician assigns a score to each exercise in FFT. The individual’s fitness is assessed based on these scores. At present, FFT is performed in the presence of a trained physician. The overall goal of the research presented in this thesis is to assess an individual’s fitness using a depth sensor mounted differential drive robot based on FFT without the help of a physician as a trained physician might not be always available and even if one is available, having one around every time is expensive. The robot autonomously navigates through the testing facility, tracks the user, assists the user performing FFT and saves the data in user file for further evaluation. The results received from the FFT is evaluated to measure the performance of the user. This data is also used for book keeping purposes and to track the progress of the user. This research is also concerned with integrating this setup with a smart home facility where all the data is stored in a central server.