• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 108
  • 20
  • 15
  • 15
  • 4
  • 2
  • 1
  • 1
  • 1
  • Tagged with
  • 234
  • 234
  • 234
  • 83
  • 55
  • 43
  • 37
  • 36
  • 31
  • 29
  • 28
  • 26
  • 25
  • 24
  • 23
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The ‘fluidity’ of beings portrayed through human-robot interaction: an analysis of human-to-Roomba robot relations

Gorea, Michelle 16 September 2014 (has links)
Based on my analysis, I found that there are a variety of ways in which individuals interact with and emotionally engage with their Roomba iRobots, via participation in a brand community or through forms of anthropomorphism such as treating it as a pet or human. I explain that there is a spectrum regarding the extent to which individuals anthropomorphize their Roomba and emotionally engage with the device. The thesis concludes with the finding that some individuals emotionally engage with their Roomba in a significant way, while others desire a disconnection from their device. I end with the suggestion that sociologists continue to consider the implications of people’s increasing interactions with technological objects and further investigate different areas of human-robot emotional connection.
2

Probabilistic Human-Robot Information Fusion

Kaupp, Tobias January 2008 (has links)
PhD / This thesis is concerned with combining the perceptual abilities of mobile robots and human operators to execute tasks cooperatively. It is generally agreed that a synergy of human and robotic skills offers an opportunity to enhance the capabilities of today’s robotic systems, while also increasing their robustness and reliability. Systems which incorporate both human and robotic information sources have the potential to build complex world models, essential for both automated and human decision making. In this work, humans and robots are regarded as equal team members who interact and communicate on a peer-to-peer basis. Human-robot communication is addressed using probabilistic representations common in robotics. While communication can in general be bidirectional, this work focuses primarily on human-to-robot information flow. More specifically, the approach advocated in this thesis is to let robots fuse their sensor observations with observations obtained from human operators. While robotic perception is well-suited for lower level world descriptions such as geometric properties, humans are able to contribute perceptual information on higher abstraction levels. Human input is translated into the machine representation via Human Sensor Models. A common mathematical framework for humans and robots reinforces the notion of true peer-to-peer interaction. Human-robot information fusion is demonstrated in two application domains: (1) scalable information gathering, and (2) cooperative decision making. Scalable information gathering is experimentally demonstrated on a system comprised of a ground vehicle, an unmanned air vehicle, and two human operators in a natural environment. Information from humans and robots was fused in a fully decentralised manner to build a shared environment representation on multiple abstraction levels. Results are presented in the form of information exchange patterns, qualitatively demonstrating the benefits of human-robot information fusion. The second application domain adds decision making to the human-robot task. Rational decisions are made based on the robots’ current beliefs which are generated by fusing human and robotic observations. Since humans are considered a valuable resource in this context, operators are only queried for input when the expected benefit of an observation exceeds the cost of obtaining it. The system can be seen as adjusting its autonomy at run-time based on the uncertainty in the robots’ beliefs. A navigation task is used to demonstrate the adjustable autonomy system experimentally. Results from two experiments are reported: a quantitative evaluation of human-robot team effectiveness, and a user study to compare the system to classical teleoperation. Results show the superiority of the system with respect to performance, operator workload, and usability.
3

A simulated robot versus a real robot: an exploration of how robot embodiment impacts people's empathic responses

Seo, Stela 03 February 2015 (has links)
In designing and evaluating human-robot interactions and interfaces, researchers often use simulated robots because of the high cost of physical robots and time required to program them. However, it is important to consider how interaction with a simulated robot differs from a real robot; that is, do simulated robots provide authentic interaction? We contribute to a growing body of work that explores this question and maps out simulated-versus-real differences, by explicitly investigating empathy: how people empathize with a physical or simulated robot when something bad happens to it. Empathy is particularly relevant to social human-robot interaction (HRI) and is integral to, e.g., companion and care robots. To explore our question, we develop a convincing HRI scenario that induces people’s empathy toward a robot, and explore psychology work for an empathy-measuring instrument. To formally evaluate our scenario and the empathy-measuring instrument in HRI scenario, we conduct a comparative user study: in one condition, participants have the scenario which induces empathy, and for the other condition, we remove any empathy inducing activities of the robot. With the validated scenario and empathy measuring instrument, we conduct another user study to explore the difference between a real and a simulated robot in terms of people’s empathic response. Our results suggest that people empathize more with a physical robot than a simulated one, a finding that has important implications on the generalizability and applicability of simulated HRI work. As part of our exploration, we additionally present an original and reproducible HRI experimental design to induce empathy toward robots, and experimentally validated an empathy-measuring instrument from psychology for use with HRI.
4

Probabilistic Human-Robot Information Fusion

Kaupp, Tobias January 2008 (has links)
PhD / This thesis is concerned with combining the perceptual abilities of mobile robots and human operators to execute tasks cooperatively. It is generally agreed that a synergy of human and robotic skills offers an opportunity to enhance the capabilities of today’s robotic systems, while also increasing their robustness and reliability. Systems which incorporate both human and robotic information sources have the potential to build complex world models, essential for both automated and human decision making. In this work, humans and robots are regarded as equal team members who interact and communicate on a peer-to-peer basis. Human-robot communication is addressed using probabilistic representations common in robotics. While communication can in general be bidirectional, this work focuses primarily on human-to-robot information flow. More specifically, the approach advocated in this thesis is to let robots fuse their sensor observations with observations obtained from human operators. While robotic perception is well-suited for lower level world descriptions such as geometric properties, humans are able to contribute perceptual information on higher abstraction levels. Human input is translated into the machine representation via Human Sensor Models. A common mathematical framework for humans and robots reinforces the notion of true peer-to-peer interaction. Human-robot information fusion is demonstrated in two application domains: (1) scalable information gathering, and (2) cooperative decision making. Scalable information gathering is experimentally demonstrated on a system comprised of a ground vehicle, an unmanned air vehicle, and two human operators in a natural environment. Information from humans and robots was fused in a fully decentralised manner to build a shared environment representation on multiple abstraction levels. Results are presented in the form of information exchange patterns, qualitatively demonstrating the benefits of human-robot information fusion. The second application domain adds decision making to the human-robot task. Rational decisions are made based on the robots’ current beliefs which are generated by fusing human and robotic observations. Since humans are considered a valuable resource in this context, operators are only queried for input when the expected benefit of an observation exceeds the cost of obtaining it. The system can be seen as adjusting its autonomy at run-time based on the uncertainty in the robots’ beliefs. A navigation task is used to demonstrate the adjustable autonomy system experimentally. Results from two experiments are reported: a quantitative evaluation of human-robot team effectiveness, and a user study to compare the system to classical teleoperation. Results show the superiority of the system with respect to performance, operator workload, and usability.
5

Understanding older adults' perceptions of usefulness of an assistive home robot

Beer, Jenay M. 13 January 2014 (has links)
Developing robots that are useful to older adults is more than simply creating robots that complete household tasks. To ensure that older adults perceive a robot to be useful, careful consideration of the users’ capabilities, robot autonomy, and task is needed (Venkatesh & Davis, 2000). The purpose of this study was to investigate the construct of perceived usefulness within the context of robot assistance. Mobile older adults (N = 12) and older adults with mobility loss (N=12) participated in an autonomy selection think aloud task, and a persona based interview. Findings suggest that older adults with mobility loss preferred an autonomy level where they command/control the robot themselves. Mobile older adults’ preferences were split between commanding/controlling the robot themselves, or the robot commands/controls itself. Reasons for their preferences were related to decision making, and were task specific. Additionally, findings from the persona base interview study support Technology Acceptance Model (TAM) constructs, as well as adaptability, reliability, and trust as positively correlated with perceptions of usefulness. However, despite the positive correlation, barriers and facilitators of acceptance identified in the interview suggest that perceived usefulness judgments are complex, and some questionnaire constructs were interpreted differently between participants. Thus, care should be taken when applying TAM constructs to other domains, such as robot assistance to promote older adult independence.
6

Framework For Robot-Assisted Doffing of Personal Protective Equipment

Umali, Antonio 19 August 2016 (has links)
"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."
7

A Collaborative Approach for Real-Time Measurements of Human Trust, Satisfaction and Frustration in Human-Robot Teaming

Unknown Date (has links)
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
8

An exploratory study of health professionals' attitudes about robotic telepresence technology

Kristoffersson, Annica, Coradeschi, Silvia, Loutfi, Amy, Severinson Eklundh, Kerstin January 2011 (has links)
This article presents the results from a video-based evaluation study of a social robotic telepresence solution for elderly. The evaluated system is a mobile teleoperated robot called Giraff that allows caregivers to virtually enter a home and conduct a natural visit just as if they were physically there. The evaluation focuses on the perspectives from primary healthcare organizations and collects the feedback from different categories of health professionals. The evaluation included 150 participants and yielded unexpected results with respect to the acceptance of the Giraff system. In particular, greater exposure to technology did not necessarily increase acceptance and large variances occurred between the categories of health professionals. In addition to outlining the results, this study provides a number of indications with respect to increasing acceptance for technology for elderly. / <p>The final version of this article can be read at http://www.tandfonline.com/doi/pdf/10.1080/15228835.2011.639509</p>
9

APPLYING THE APPRAISAL THEORY OF EMOTIONTO HUMAN-AGENT INTERACTION

Pepe, Aaron 18 September 2007 (has links)
Autonomous robots are increasingly being used in everyday life; cleaning our floors, entertaining us and supplementing soldiers in the battlefield. As emotion is a key ingredient in how we interact with others, it is important that our emotional interaction with these new entities be understood. This dissertation proposes using the appraisal theory of emotion (Roseman, Scherer, Schorr, & Johnstone, 2001) to investigate how we understand and evaluate situations involving this new breed of robot. This research involves two studies; in the first study an experimental method was used in which participants interacted with a live dog, a robotic dog or a non-anthropomorphic robot to attempt to accomplish a set of tasks. The appraisals of motive consistent / motive inconsistent (the task was performed correctly/incorrectly) and high / low perceived control (the teammate was well trained/not well trained) were manipulated to show the practicality of using appraisal theory as a basis for human robot interaction studies. Robot form was investigated for its influence on emotions experienced. Finally, the influence of high and low control on the experience of positive emotions caused by another was investigated. Results show that a human &#150; robot live interaction test bed is a valid way to influence participants' appraisals. Manipulation checks of motive consistent / motive inconsistent, high / low perceived control and the proper appraisal of cause were significant. Form was shown to influence both the positive and negative emotions experienced, the more lifelike agents were rated higher in positive emotions and lower in negative emotions. The emotion gratitude was shown to be greater during conditions of low control when the entities performed correctly,suggesting that more experiments should be conducted investigating agent caused motive-conducive events. A second study was performed with participants evaluating their reaction to a hypothetical story. In this story they were interacting with either a human, robotic dog, or robot to complete a task. These three agent types and high/low perceived control were manipulated with all stories ending successfully. Results indicated that gratitude and appreciation are sensitive to the manipulation of agent type. It is suggested that, based on the results of these studies, the emotion gratitude should be added to Roseman et al. (2001) appraisal theory to describe the emotion felt during low-control, motive-consistent, other-caused events. These studies have also shown that the appraisal theory of emotion is useful in the study of human-robot and human-animal interactions. / Ph.D. / Department of Psychology / Sciences / Modeling and Simulation PhD
10

THE IMPACT OF MENTAL TRANSFORMATION TRAINING ACROSS LEVELS OF AUTOMATION ON SPATIAL AWARENESS IN HUMAN-ROBOT INTERACTION

Rehfeld, Sherri 11 January 2007 (has links)
One of the problems affecting robot operators' spatial awareness involves their ability to infer a robot's location based on the views from on-board cameras and other electro-optic systems. To understand the vehicle's location, operators typically need to translate images from a vehicle's camera into some other coordinates, such as a location on a map. This translation requires operators to relate the view by mentally rotating it along a number of axes, a task that is both attention-demanding and workload-intensive, and one that is likely affected by individual differences in operator spatial abilities. Because building and maintaining spatial awareness is attention-demanding and workload-intensive, any variable that changes operator workload and attention should be investigated for its effects on operator spatial awareness. One of these variables is the use of automation (i.e., assigning functions to the robot). According to Malleable Attentional Resource Theory (MART), variation in workload across levels of automation affects an operator's attentional capacity to process critical cues like those that enable an operator to understand the robot's past, current, and future location. The study reported here focused on performance aspects of human-robot interaction involving ground robots (i.e., unmanned ground vehicles, or UGVs) during reconnaissance tasks. In particular, this study examined how differences in operator spatial ability and in operator workload and attention interacted to affect spatial awareness during human-robot interaction (HRI). Operator spatial abilities were systematically manipulated through the use of mental transformation training. Additionally, operator workload and attention were manipulated via the use of three different levels of automation (i.e., manual control, decision support, and full automation). Operator spatial awareness was measured by the size of errors made by the operators, when they were tasked to infer the robot's location from on-board camera views at three different points in a sequence of robot movements through a simulated military operation in urban terrain (MOUT) environment. The results showed that mental transformation training increased two areas of spatial ability, namely mental rotation and spatial visualization. Further, spatial ability in these two areas predicted performance in vehicle localization during the reconnaissance task. Finally, assistive automation showed a benefit with respect to operator workload, situation awareness, and subsequently performance. Together, the results of the study have implications with respect to the design of robots, function allocation between robots and operators, and training for spatial ability. Future research should investigate the interactive effects on operator spatial awareness of spatial ability, spatial ability training, and other variables affecting operator workload and attention. / Ph.D. / Department of Psychology / Sciences / Psychology

Page generated in 0.0977 seconds