PCB Origami: A Material-Based Design Approach to Computer-Aided Foldable Electronic Devices

Origami is traditionally implemented in paper, which is a passive material. This research explores the use of material with embedded electronics such as printed circuit boards (PCB) as the medium for origami folding to create an interactive folding experience and to generate foldable objects with added functionalities. PCBs are produced as 2D shapes. By folding PCB arrays, it is possible to create 3D objects that contain electronic functions. Conductivity, output devices (such as light emitting diodes) and microcontroller computation can create an interactive folding experience, for user guidance and verification of the folding. We call this approach and methodology PCB origami. The work presented in this paper describes two unique interaction and fabrication techniques for creating and folding electronic materials. We demonstrate prototypes and present verification/evaluation strategies for guiding the user through the folding process

Designing Origami-Adapted Deployable Modules for Soft Continuum Arms

© Springer Nature Switzerland AG 2019. Origami has several attractive attributes including deployability and portability which have been extensively adapted in designs of robotic devices. Drawing inspiration from foldable origami structures, this paper presents an engineering design process for fast making deployable modules of soft continuum arms. The process is illustrated with an example which adapts a modified accordion fold pattern to a lightweight deployable module. Kinematic models of the four-sided Accordion fold pattern is explored in terms of mechanism theory. Taking account of both the kinematic model and the materials selection, a 2D flat sheet model of the four-sided Accordion fold pattern is obtained for 3D printing. Following the design process, the deployable module is then fabricated by laminating 3D printed origami skeleton and flexible thermoplastic polyurethane (TPU) coated fabric. Preliminary tests of the prototype shown that the folding motion are enabled mainly by the flexible fabric between the gaps of thick panels of the origami skeleton and matches the kinematic analysis. The proposed approach has advantages of quick scaling dimensions, cost effective and fast fabricating thus allowing adaptive design according to specific demands of various tasks

The Teaching Candidates’ Views About the Impact of Origami-Supported Geometry Teaching on Comprehending the Description, Axiom and Theorem

This study has been made in the purpose of revealing the elementary mathematics teaching candidates’ views about the impact of origami-supported geometry teaching on comprehending the description, axiom and theorem. The study group consists of 52 mathematics teaching candidate. A questionnary which consists of the open-ended questions has been used in the study which has been made with the use of study case design which is one of the qualitative research methods. The impact of origami-supported teaching on understanding the geometry has been interrogated in the questions which have been asked. According to the findings which have been obtained, the teaching candidates have shared the impact of origami-supported geometry teaching on the description, axiom and theorem as they have explained through their own experiences. They have mentioned on these sharings especially that the relation between the description and concept, the relation between the axiom and theorem and the relation between the description and theorem are correctly stated mathematically. As a result of the research, it can be said that the use of origami-supported teaching facilitate to understand its axiomatic structure especially in order that Euclides geometry is comprehended, it can support to interrogate the geometry knowledge correctly and as its result, it can positively affect on the Vam Heile geometry thinking levels. Keywords: Origami, geometry teaching, description-axiom-theorem, teaching candidates’ view

Exploring local regularities for 3D object recognition

In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces (L-MSDAF), localized minimum sum of segment magnitudes of common edges (L-MSSM), and localized minimum sum of areas of child face (L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness

Environmental Relations in Image Understanding: The Force of Gravity

This paper shows how assumptions and information concerning the external world properties of horizontal and vertical can aid in the analysis of images, even at the very lowest levels of processing. First, the author reviews the pervasiveness of the force of gravity, and its influence on most natural image understanding systems. Next, he derives several fundamental mathematical results relating phenomena in both the gradient space and the images space to the external world attributes of horizontal and vertical. He then shows how these results interrelate three imaging phenomena: the surfaces in the image, the external sensor parameters, and the environmental labels. It is detailed how, in general, specific information regarding any two of these phenomena can be used to quantitatively derive the third; occasionally one can do even better. Algorithms for such quantitative derivations are presented, including two based on the Hough transform. The author further shows how certain environmental perpendicularities can be exploited very efficiently, and even elegantly: ordinarily complex math simplifies to the extent that environmental distances can be directly read off the image. The power of such environmental labels is then demonstrated by an analysis of the source of ambiguity in a simple illusion-like image configuration. The paper concludes with an analysis of the class of heuristics that have been invoked throughout. They are seen to be instantiations of the shape-from-texture meta-heuristics that "near implies preferred" and "preferred implies simple.

Towards Scene Understanding with Detailed 3D Object Representations

Current approaches to semantic image and scene understanding typically employ rather simple object representations such as 2D or 3D bounding boxes. While such coarse models are robust and allow for reliable object detection, they discard much of the information about objects' 3D shape and pose, and thus do not lend themselves well to higher-level reasoning. Here, we propose to base scene understanding on a high-resolution object representation. An object class - in our case cars - is modeled as a deformable 3D wireframe, which enables fine-grained modeling at the level of individual vertices and faces. We augment that model to explicitly include vertex-level occlusion, and embed all instances in a common coordinate frame, in order to infer and exploit object-object interactions. Specifically, from a single view we jointly estimate the shapes and poses of multiple objects in a common 3D frame. A ground plane in that frame is estimated by consensus among different objects, which significantly stabilizes monocular 3D pose estimation. The fine-grained model, in conjunction with the explicit 3D scene model, further allows one to infer part-level occlusions between the modeled objects, as well as occlusions by other, unmodeled scene elements. To demonstrate the benefits of such detailed object class models in the context of scene understanding we systematically evaluate our approach on the challenging KITTI street scene dataset. The experiments show that the model's ability to utilize image evidence at the level of individual parts improves monocular 3D pose estimation w.r.t. both location and (continuous) viewpoint.Comment: International Journal of Computer Vision (appeared online on 4 November 2014). Online version: http://link.springer.com/article/10.1007/s11263-014-0780-