In robot teaching, the grasping strategies taught to robots by users are critical information, because these strategies contain the implicit knowledge necessary to successfully perform a series of manipulations;howeve...
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In robot teaching, the grasping strategies taught to robots by users are critical information, because these strategies contain the implicit knowledge necessary to successfully perform a series of manipulations;however, limited practical knowledge exists on how to utilize linguistic information for supporting grasp-type recognition in multimodal teaching. This study focused on the effects of text-driven object affordance-a prior distribution of grasp types for each object-on image-based grasp-type recognition. To this end, we created the datasets of first-person grasping-hand images labeled with grasp types and object names and tested if the object affordance enhanced the performance of image-based recognition. We evaluated two scenarios with real and illusory objects to be grasped, considering a teaching condition in mixed reality, where the lack of visual object information can make image-based recognition challenging. The results show that object affordance guided the image-based recognition in two scenarios, that is, increasing the recognition accuracy by (1) excluding the unlikely grasp types from the candidates and (2) enhancing the likely grasp types. Additionally, the "enhancing effect" was more pronounced with greater grasp-type bias for each object in a test dataset. These results indicate the effectiveness of object affordance for guiding grasp-type recognition in multimodal robot teaching applications. The contributions of this study are (1) demonstrating the effectiveness of object affordance in guiding grasp-type recognition both with and without the real objects in images, (2) demonstrating the conditions under which the merits of object affordance are pronounced, and (3) providing a dataset of first-person grasping images labeled with possible grasp types for each object.
This paper presents a bottom-up approach to designing and developing a high-fidelity simulation environment that fosters human acceptance of artificial intelligence (AI) as teammates by refining their mental models of...
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This paper presents a bottom-up approach to designing and developing a high-fidelity simulation environment that fosters human acceptance of artificial intelligence (AI) as teammates by refining their mental models of appropriate teamwork expectations. Our process begins by first identifying an appropriate contextual situation that warrants humans teaming with AI as opposed to other team-based configurations. Those criteria are based on the delegation of roles appropriate to the established strengths of humans/AI, as well as the interdependence created between those roles to accentuate the expectations of teammate behavior. Next, qualitative interviews should be conducted with diverse subject matter experts to gain a comprehensive understanding of the situation and the environmental attributes through various perspectives. Once analyzed using thematic analysis, themes present themselves as design recommendations on how to create a high-fidelity simulation environment that nurtures human-agent team collaboration.
The advancements in terms of networking, image resolution, computer vision (CV) and mobile cloud computing performances are transforming Mobile Augmented Reality (MAR) into a technology which may be put to good use in...
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ISBN:
(纸本)9781450384780
The advancements in terms of networking, image resolution, computer vision (CV) and mobile cloud computing performances are transforming Mobile Augmented Reality (MAR) into a technology which may be put to good use in a variety of everyday contexts. To make this point, we here consider an artisanal craft rooted back into the past, key locksmithing, and show how today MAR capabilities may simplify and ameliorate the performances of such ancient trade. To this aim, we introduce the requirements posed by such craft and present a MAR-based workflow which may be implemented to support and speed its execution. This could also impact the everyday lives of ordinary citizens, since it pose the bases of remote locksmithing activities.
The determination of destinations and paths is a critical aspect of robot navigation. In recent years, research has been conducted on methods to provide robots with realistic destinations for use in practical situatio...
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The determination of destinations and paths is a critical aspect of robot navigation. In recent years, research has been conducted on methods to provide robots with realistic destinations for use in practical situations. One such general method is a spatial search based on limited information such as the name of the target object or a photograph of the destination. However, if the rough location of the destination is known from the viewpoint of an instructor, and can be communicated to the robot, then it is possible to reduce the search load on the robot. Therefore, in this study, we propose a new task that integrates the pointed instructions of an operator using and augmented reality device into the robot's search route. However, the instructor may not be able to point directly to the route if it is within a blind spot. Thus, we propose a combined search method; where the pointing path is represented as a set of vectors rather than a sequence of points and used to generate a potential field which is integrated with an existing traditional robot navigation method. In this study, we evaluate the proposed method in an experiment using the 3D simulator Habitat, and show that the proposed method outperforms existing methods under the pointing path information.
Despite a growing demand for Web Development and adjacent tech skills, there is a lack of accessible skills training for screen reader users. To address this gap, we developed tools and techniques to support screen re...
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Despite a growing demand for Web Development and adjacent tech skills, there is a lack of accessible skills training for screen reader users. To address this gap, we developed tools and techniques to support screen reader users in learning web development. In this article, we describe our design, implementation, and evaluation of a nine-week web development workshop, designed to introduce screen reader users to HTML, CSS, and JavaScript. We taught the remote workshop using synchronous lectures followed by one-on-one time with Teaching Assistants (TAs) and included a resource-rich website, tactile diagrams, and discussion forum. We evaluated the effectiveness of our tools and the impact of the workshop during, immediately following, and one year after the workshop. At its conclusion, students demonstrated their knowledge of web development basics by creating and publishing their own websites;showed an increase in self-efficacy;and maintained a high level of interest in the subject. Participation also benefited TAs who reported increased confidence in understanding accessibility concepts, increased interest in pursuing work related to accessibility, and plans to apply what they learned. One year after the workshop, both students and TAs reported a lasting impact. Most notably, students had applied their understanding of design concepts, reported that the workshop helped them prepare for career changes or helped them in their current job functions, and that it gave them both the language and confidence to problem-solve web and accessibility issues. TAs felt that the workshop broadened their understanding of blind students' abilities;especially when provided with accessible materials and tools, it gave them a better understanding of digital accessibility and assistive technologies, and they shared examples of how they continue to apply learnings and advocate for accessibility. Based on these findings, we recommend techniques and tools to support screen reader users' lea
Mixed reality (MR) approaches offer merging of real and virtual worlds to create new environments and visualizations for real-time interaction. Existing MR systems, however, do not utilise user real environment, lack ...
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ISBN:
(纸本)9781665484022
Mixed reality (MR) approaches offer merging of real and virtual worlds to create new environments and visualizations for real-time interaction. Existing MR systems, however, do not utilise user real environment, lack detail in dynamic environments, and often lack multi-user capabilities. This research focuses on exploring multiuser aspects of immersive collaboration, where an arbitrary number of co-located and remotely located users can collaborate in a single or merged collaborative MR space. The aim is to enable users to experience VR/AR together, irrespective of the type of HMD, and facilitate users with their collaborative tasks. The main goal is to develop an immersive collaboration platform in which users can utilize the space around them and at the same time collaborate and switch between different perspectives of other co-located and remote users.
Knowledge workers typically work on some kind of computer and other than an internet connection, they rarely need access to specific work environments or devices. This makes it feasible for them to also work in differ...
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ISBN:
(纸本)9781665484022
Knowledge workers typically work on some kind of computer and other than an internet connection, they rarely need access to specific work environments or devices. This makes it feasible for them to also work in different environments or in mobile settings, like public transportation. In such spaces comfort and productivity could be decreased due to hardware limitations like small screen sizes or input devices and environmental clutter. Mixed reality (MR) has the potential to solve such issues. It can provide the user with additional display space that can even include the third dimension. It can open up new possibilities for interacting with virtual content using gestures or spatially tracked devices. And it can allow the users to modify the work environment according to their personal preferences. This doctoral thesis aims at exploring the challenges of using MR for mobile knowledge work and how to effectively support knowledge worker tasks through appropriate interaction techniques.
Accompanying a data visualization with metadata may benefit readers by facilitating content understanding, strengthening trust, and providing accountability. However, providing this kind of information may also have n...
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ISBN:
(纸本)9781665413664
Accompanying a data visualization with metadata may benefit readers by facilitating content understanding, strengthening trust, and providing accountability. However, providing this kind of information may also have negative, unintended consequences, such as biasing readers' interpretations, a loss of trust as a result of too much transparency, and the possibility of opening visualization creators with minoritized identities up to undeserved critique. To help future visualization researchers and practitioners decide what kinds of metadata to include, we discuss some of the potential benefits and risks of disclosing five kinds of metadata: metadata about the source of the underlying data;the cleaning and processing conducted;the marks, channels, and other design elements used;the people who directly created the visualization;and the people for whom the visualization was created. We conclude by proposing a few open research questions related to how to communicate metadata about visualizations.
In this paper, we provide an approach on using behavioral biometrics to perform cross-system high-assurance authentication of users in virtual reality (VR) environments. VR is currently being explored as a critical to...
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ISBN:
(纸本)9781665418386
In this paper, we provide an approach on using behavioral biometrics to perform cross-system high-assurance authentication of users in virtual reality (VR) environments. VR is currently being explored as a critical tool to ensure seamless delivery of essential services, such as education, healthcare, and personal finance, while enabling users to work from home environments. Due to the sensitive nature of personal data generated, VR applications for essential services need to provide secure access. Traditional PIN or password-based credentials can be breached by malicious impostors, or be handed over by an intended user of a VR system to a confederate to assist the intended user in completing a task, e.g., an exam or a physical therapy routine. Existing approaches that use the behavior of the user in VR as a biometric signature fail when users provide enrollment and use-time data on different VR systems. We use Siamese neural networks to learn a distance function that characterizes the systematic differences between data provided across pairs of dissimilar VR systems. Our approach provides average equal error rates (EERs) ranging from 1.38% to 3.86% for authentication using a benchmark dataset that consists of 41 users performing a ball-throwing task with 3 VR systems-an Oculus Quest, an HTC Vive, and an HTC Vive Cosmos. To compare to prior approaches in VR biometrics, we also obtain average accuracies for the task of identification, where given an input user's trajectory in a use-time VR system, we use Siamese networks to return the user with the top matching trajectory in an enrollment VR system as the label. We report identification results ranging from 87.82% to 98.53% with average improvements of 29.78%+/- 8.58% and 30.78%+/- 3.68% over existing approaches that use generic distance matching and fully convolutional networks on the enrollment dataset respectively.
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