Constructing sonified haptic line graphs for the blind student: first steps

Line graphs stand as an established information visualisation and analysis technique taught at various levels of difficulty according to standard Mathematics curricula. It has been argued that blind individuals cannot use line graphs as a visualisation and analytic tool because they currently primarily exist in the visual medium. The research described in this paper aims at making line graphs accessible to blind students through auditory and haptic media. We describe (1) our design space for representing line graphs, (2) the technology we use to develop our prototypes and (3) the insights from our preliminary work

Improving grasping forces during the manipulation of unknown objects

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksMany of the solutions proposed for the object manipulation problem are based on the knowledge of the object features. The approach proposed in this paper intends to provide a simple geometrical approach to securely manipulate an unknown object based only on tactile and kinematic information. The tactile and kinematic data obtained during the manipulation is used to recognize the object shape (at least the local object curvature), allowing to improve the grasping forces when this information is added to the manipulation strategy. The approach has been fully implemented and tested using the Schunk Dexterous Hand (SDH2). Experimental results are shown to illustrate the efficiency of the approach.Peer ReviewedPostprint (author's final draft

Molyneux's Question Within and Across the Senses

This chapter explores how our understanding of Molyneux’s question, and of the possibility of an experimental resolution to it, should be affected by recognizing the complexity that is involved in reidentifying shapes and other spatial properties across differing sensory manifestations of them. I will argue that while philosophers today usually treat the question as concerning ‘the relations between perceptions of shape in different sensory modalities’ (Campbell 1995, 301), in fact this is only part of the question’s real interest, and that the answer to the question also turns on how shape is perceived within each of sight and touch individually

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

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 participants’ 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

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

A Model that Predicts the Material Recognition Performance of Thermal Tactile Sensing

Tactile sensing can enable a robot to infer properties of its surroundings, such as the material of an object. Heat transfer based sensing can be used for material recognition due to differences in the thermal properties of materials. While data-driven methods have shown promise for this recognition problem, many factors can influence performance, including sensor noise, the initial temperatures of the sensor and the object, the thermal effusivities of the materials, and the duration of contact. We present a physics-based mathematical model that predicts material recognition performance given these factors. Our model uses semi-infinite solids and a statistical method to calculate an F1 score for the binary material recognition. We evaluated our method using simulated contact with 69 materials and data collected by a real robot with 12 materials. Our model predicted the material recognition performance of support vector machine (SVM) with 96% accuracy for the simulated data, with 92% accuracy for real-world data with constant initial sensor temperatures, and with 91% accuracy for real-world data with varied initial sensor temperatures. Using our model, we also provide insight into the roles of various factors on recognition performance, such as the temperature difference between the sensor and the object. Overall, our results suggest that our model could be used to help design better thermal sensors for robots and enable robots to use them more effectively.Comment: This article is currently under review for possible publicatio

The roots of self-awareness

In this paper we provide an account of the structural underpinnings of self-awareness. We offer both an abstract, logical account-by way of suggestions for how to build a genuinely self-referring artificial agent-and a biological account, via a discussion of the role of somatoception in supporting and structuring self-awareness more generally. Central to the account is a discussion of the necessary motivational properties of self-representing mental tokens, in light of which we offer a novel definition of self-representation. We also discuss the role of such tokens in organizing self-specifying information, which leads to a naturalized restatement of the guarantee that introspective awareness is immune to error due to mis-identification of the subject