24,744 research outputs found

    Symmetric and asymmetric action integration during cooperative object manipulation in virtual environments

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    Cooperation between multiple users in a virtual environment (VE) can take place at one of three levels. These are defined as where users can perceive each other (Level 1), individually change the scene (Level 2), or simultaneously act on and manipulate the same object (Level 3). Despite representing the highest level of cooperation, multi-user object manipulation has rarely been studied. This paper describes a behavioral experiment in which the piano movers' problem (maneuvering a large object through a restricted space) was used to investigate object manipulation by pairs of participants in a VE. Participants' interactions with the object were integrated together either symmetrically or asymmetrically. The former only allowed the common component of participants' actions to take place, but the latter used the mean. Symmetric action integration was superior for sections of the task when both participants had to perform similar actions, but if participants had to move in different ways (e.g., one maneuvering themselves through a narrow opening while the other traveled down a wide corridor) then asymmetric integration was superior. With both forms of integration, the extent to which participants coordinated their actions was poor and this led to a substantial cooperation overhead (the reduction in performance caused by having to cooperate with another person)

    Designing Hybrid Interactions through an Understanding of the Affordances of Physical and Digital Technologies

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    Two recent technological advances have extended the diversity of domains and social contexts of Human-Computer Interaction: the embedding of computing capabilities into physical hand-held objects, and the emergence of large interactive surfaces, such as tabletops and wall boards. Both interactive surfaces and small computational devices usually allow for direct and space-multiplex input, i.e., for the spatial coincidence of physical action and digital output, in multiple points simultaneously. Such a powerful combination opens novel opportunities for the design of what are considered as hybrid interactions in this work. This thesis explores the affordances of physical interaction as resources for interface design of such hybrid interactions. The hybrid systems that are elaborated in this work are envisioned to support specific social and physical contexts, such as collaborative cooking in a domestic kitchen, or collaborative creativity in a design process. In particular, different aspects of physicality characteristic of those specific domains are explored, with the aim of promoting skill transfer across domains. irst, different approaches to the design of space-multiplex, function-specific interfaces are considered and investigated. Such design approaches build on related work on Graspable User Interfaces and extend the design space to direct touch interfaces such as touch-sensitive surfaces, in different sizes and orientations (i.e., tablets, interactive tabletops, and walls). These approaches are instantiated in the design of several experience prototypes: These are evaluated in different settings to assess the contextual implications of integrating aspects of physicality in the design of the interface. Such implications are observed both at the pragmatic level of interaction (i.e., patterns of users' behaviors on first contact with the interface), as well as on user' subjective response. The results indicate that the context of interaction affects the perception of the affordances of the system, and that some qualities of physicality such as the 3D space of manipulation and relative haptic feedback can affect the feeling of engagement and control. Building on these findings, two controlled studies are conducted to observe more systematically the implications of integrating some of the qualities of physical interaction into the design of hybrid ones. The results indicate that, despite the fact that several aspects of physical interaction are mimicked in the interface, the interaction with digital media is quite different and seems to reveal existing mental models and expectations resulting from previous experience with the WIMP paradigm on the desktop PC

    Goal Set Inverse Optimal Control and Iterative Re-planning for Predicting Human Reaching Motions in Shared Workspaces

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    To enable safe and efficient human-robot collaboration in shared workspaces it is important for the robot to predict how a human will move when performing a task. While predicting human motion for tasks not known a priori is very challenging, we argue that single-arm reaching motions for known tasks in collaborative settings (which are especially relevant for manufacturing) are indeed predictable. Two hypotheses underlie our approach for predicting such motions: First, that the trajectory the human performs is optimal with respect to an unknown cost function, and second, that human adaptation to their partner's motion can be captured well through iterative re-planning with the above cost function. The key to our approach is thus to learn a cost function which "explains" the motion of the human. To do this, we gather example trajectories from pairs of participants performing a collaborative assembly task using motion capture. We then use Inverse Optimal Control to learn a cost function from these trajectories. Finally, we predict reaching motions from the human's current configuration to a task-space goal region by iteratively re-planning a trajectory using the learned cost function. Our planning algorithm is based on the trajectory optimizer STOMP, it plans for a 23 DoF human kinematic model and accounts for the presence of a moving collaborator and obstacles in the environment. Our results suggest that in most cases, our method outperforms baseline methods when predicting motions. We also show that our method outperforms baselines for predicting human motion when a human and a robot share the workspace.Comment: 12 pages, Accepted for publication IEEE Transaction on Robotics 201

    Collaborative Control for a Robotic Wheelchair: Evaluation of Performance, Attention, and Workload

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    Powered wheelchair users often struggle to drive safely and effectively and in more critical cases can only get around when accompanied by an assistant. To address these issues, we propose a collaborative control mechanism that assists the user as and when they require help. The system uses a multiple–hypotheses method to predict the driver’s intentions and if necessary, adjusts the control signals to achieve the desired goal safely. The main emphasis of this paper is on a comprehensive evaluation, where we not only look at the system performance, but, perhaps more importantly, we characterise the user performance, in an experiment that combines eye–tracking with a secondary task. Without assistance, participants experienced multiple collisions whilst driving around the predefined route. Conversely, when they were assisted by the collaborative controller, not only did they drive more safely, but they were able to pay less attention to their driving, resulting in a reduced cognitive workload. We discuss the importance of these results and their implications for other applications of shared control, such as brain–machine interfaces, where it could be used to compensate for both the low frequency and the low resolution of the user input

    Tangible user interfaces : past, present and future directions

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    In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

    Using Auto-Ordering to Improve Object Transfer between Mobile Devices

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    People frequently form small groups in many social and professional situations: from conference attendees meeting at a coffee break, to siblings gathering at a family barbecue. These ad-hoc gatherings typically form into predictable geometries based on circles or circular arcs (called F-Formations). Because our lives are increasingly stored and represented by data on handheld devices, the desire to be able to share digital objects while in these groupings has increased. Using the relative position in these groups to facilitate file sharing could facilitate intuitive interfaces such as passing or flicking. However, there is no reliable, lightweight, ad-hoc technology for detecting and representing relative locations around a circle. In this thesis, we present three systems that can auto-order locations about a circle based on sensors standard on commodity smartphones. We tested two of these systems using an object passing task in a laboratory environment against unordered and proximity-based systems, and show that our techniques are faster, more accurate, and preferred by users
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