Search for: All records

We present a novel methodology to generate mechanical structures based on fractal geometry using the chaos game, which generates self-similar point-sets within a polygon. Using the Voronoi decomposition of these points, we are able to generate groups of self-similar structures that can be related back to their chaos game parameters, namely, the polygonal domain, fractional distance, and number of samples. Our approach explores the use of forward design of generative structures, which in some cases can be easier to use for designing than inverse generative design techniques. To this end, the central hypothesis of our work is that structures generated using the chaos game can generate families of self-similar structures that, while not identical, exhibit similar mechanical behavior in a statistical sense. We present a systematic study of these self-similar structures through modal analysis and tensile loading and demonstrate a preliminary confirmation of our hypothesis.

 

We present a novel methodology to generate mechanical structures based on the idea of fractal geometry as described by the chaos game. Chaos game is an iterative method that generates self-similar point-sets in the limiting case within a polygonal domain. By computing Voronoi tessellations on these point-sets, our method generates mechanical structures that adopts the self-similarity of the point-sets resulting in fractal distribution of local stiffness. The motivation behind our approach comes from the observation that a typical generative structural design workflow requires the ability to generate families of structures that possess shared behavioral (e.g. thermal, mechanical, etc.) characteristics making each structure distinct but feasible. However, the generation of the alternatives, almost always, requires solving an inverse structural problem which is both conceptually and computationally challenging. The objective of our work is to develop and investigate a forward-design methodology for generating families of structures that, while not identical, exhibit similar mechanical behavior in a statistical sense. To this end, the central hypothesis of our work is that structures generated using the chaos game can generate families of self-similar structures that, while not identical, exhibit similar mechanical behavior in a statistical sense. Furthermore, each family is uniquely identifiable from the parameters of the chaos game, namely, the polygonal domain, fractional distance, and number of samples. We present a systematic study of these self-similar structures through modal analysis and demonstrate a preliminary confirmation of our hypothesis.

 

Abstract We present an experimental investigation of spatial audio feedback using smartphones to support direction localization in pointing tasks for people with visual impairments (PVIs). We do this using a mobile game based on a bow-and-arrow metaphor. Our game provides a combination of spatial and non-spatial (sound beacon) audio to help the user locate the direction of the target. Our experiments with sighted, sighted-blindfolded, and visually impaired users shows that (a) the efficacy of spatial audio is relatively higher for PVIs than for blindfolded sighted users during the initial reaction time for direction localization, (b) the general behavior between PVIs and blind-folded individuals is statistically similar, and (c) the lack of spatial audio significantly reduces the localization performance even in sighted blind-folded users. Based on our findings, we discuss the system and interaction design implications for making future mobile-based spatial interactions accessible to PVIs. 

Abstract This article studies fine motor strategies for precise spatial manipulation in close-to-body interactions. Our innate ability for precise work is the result of the confluence of visuo-tactile perception, proprioception, and bi-manual motor control. Contrary to this, most mixed-reality (MR) systems are designed for interactions at arms length. To develop guidelines for precise manipulations in MR systems, there is a need for a systematic study of motor strategies including physical indexing, bi-manual coordination, and the relationship between visual and tactile feedback. To address this need, we present a series of experiments using three variations of a tablet-based MR interface using a close-range motion capture system and motion-tracked shape proxies. We investigate an elaborate version of the classic peg-and-hole task that our results strongly suggests the critical need for high precision tracking to enable precise manipulation. 

In this work, we introduce an approach to model topologically interlocked corrugated bricks that can be assembled in a water-tight manner (space-filling) to design a variety of spatial structures. Our approach takes inspiration from recently developed methods that utilize Voronoi tessellation of spatial domains by using symmetrically arranged Voronoi sites. However, in contrast to these existing methods, we focus our attention on Voronoi sites modeled using helical trajectories, which can provide corrugation and better interlocking. For symmetries, we only use affine transformations based on the Bravais lattice to avoid self-intersections. This methodology naturally results in structures that are both space-filling (owing to Voronoi tessellation) as well as interlocking by corrugation (owing to helical trajectories). The resulting shapes of the bricks appear to be similar to a variety of pasta noodles, thereby inspiring the names, Voronoi Spaghetti and VoroNoodles. 

Abstract In this paper, we introduce a novel prototyping workflow, QuickProbe, that enables a user to create quick-and-dirty prototypes taking direct inspiration from existing physical objects. Our workflow is inspired by the notion of prototyping-in-context using physical scaffolds in digital environments. To achieve this we introduce a simple kinesthetic-geometric curve representation wherein we integrated the geometric representation of the curve with the virtual kinesthetic feedback. We test the efficacy of this kinesthetic-geometric curve representation through a qualitative user study conducted with ten participants. In this study, users were asked to generate wire-frame curve networks on top of the physical shapes by sampling multiple control points along the surface. We conducted two different sets of experiments in this work. In the first set of experiments, users were tasked with tracing the physical shape of the object. In the second set of experiments, the goal was to explore different artistic designs that the user could draw using the physical scaffolding of the shapes. Through our user studies, we showed the variety of designs that the users were able to create. We also evaluated the similarities and differences we observed between the two different sets of experiments. We further discuss the user feedback and the possible design scenarios where our QuickProbe workflow can be used.