13,428 research outputs found

    Mid-air haptic rendering of 2D geometric shapes with a dynamic tactile pointer

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    An important challenge that affects ultrasonic midair haptics, in contrast to physical touch, is that we lose certain exploratory procedures such as contour following. This makes the task of perceiving geometric properties and shape identification more difficult. Meanwhile, the growing interest in mid-air haptics and their application to various new areas requires an improved understanding of how we perceive specific haptic stimuli, such as icons and control dials in mid-air. We address this challenge by investigating static and dynamic methods of displaying 2D geometric shapes in mid-air. We display a circle, a square, and a triangle, in either a static or dynamic condition, using ultrasonic mid-air haptics. In the static condition, the shapes are presented as a full outline in mid-air, while in the dynamic condition, a tactile pointer is moved around the perimeter of the shapes. We measure participantsā€™ accuracy and confidence of identifying shapes in two controlled experiments (n1 = 34, n2 = 25). Results reveal that in the dynamic condition people recognise shapes significantly more accurately, and with higher confidence. We also find that representing polygons as a set of individually drawn haptic strokes, with a short pause at the corners, drastically enhances shape recognition accuracy. Our research supports the design of mid-air haptic user interfaces in application scenarios such as in-car interactions or assistive technology in education

    Sensory Substitution, Key to Inclusive Learning

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    Visually impaired students, in primary education, encounter unique challenges while learning creative skills, exploring artistic expression and developing problem-solving skills, because so much instructional content is delivered visually. Sensory substitutionā€”an approach that replaces visual information with feedback from other intact senses like touch, sound, taste or smellā€”provides an opportunity to address those challenges. Through the use of sensory substitution, this thesis proposes concrete ways to capitalize on the enhanced abilities of visually impaired primary school students. The research outcome of this thesis is a system of templates that puts these enhanced abilities to work for visually impaired students, to support them while they learn creative skills and practice problem-solving in a classroom setting. Each template contains a lesson that can be learned by using the process of paper quilling. The templates work equally well for sighted and visually impaired students, since all will be able to understand the lesson by using the sense of touch, as they learn by making

    Impact of haptic 'touching' technology on cultural applications

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    Multimodal Hierarchical Dirichlet Process-based Active Perception

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    In this paper, we propose an active perception method for recognizing object categories based on the multimodal hierarchical Dirichlet process (MHDP). The MHDP enables a robot to form object categories using multimodal information, e.g., visual, auditory, and haptic information, which can be observed by performing actions on an object. However, performing many actions on a target object requires a long time. In a real-time scenario, i.e., when the time is limited, the robot has to determine the set of actions that is most effective for recognizing a target object. We propose an MHDP-based active perception method that uses the information gain (IG) maximization criterion and lazy greedy algorithm. We show that the IG maximization criterion is optimal in the sense that the criterion is equivalent to a minimization of the expected Kullback--Leibler divergence between a final recognition state and the recognition state after the next set of actions. However, a straightforward calculation of IG is practically impossible. Therefore, we derive an efficient Monte Carlo approximation method for IG by making use of a property of the MHDP. We also show that the IG has submodular and non-decreasing properties as a set function because of the structure of the graphical model of the MHDP. Therefore, the IG maximization problem is reduced to a submodular maximization problem. This means that greedy and lazy greedy algorithms are effective and have a theoretical justification for their performance. We conducted an experiment using an upper-torso humanoid robot and a second one using synthetic data. The experimental results show that the method enables the robot to select a set of actions that allow it to recognize target objects quickly and accurately. The results support our theoretical outcomes.Comment: submitte
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