A manifold operator representation for adaptive design

Beal, Jacob; Mostafa, Hala; Mozeika, Annan; Axelrod, Benjamin; Adler, Aaron; Markiewicz, Gretchen; Usbeck, Kyle

doi:10.1145/2330163.2330239

Cited by 4 publications

(4 citation statements)

References 17 publications

(18 reference statements)

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“…Finally, a new, incrementally modified design is produced from the updated parameters. For the work in this paper, we use a simple parametric adjustment; the same framework, however, can support more complex layout changes like those in (Beal et al 2012). With an appropriate choice of stress metrics, incremental updates, and blending function, a system of FBs can be applied to make incremental adjustments to the design of an electromechanical system.…”

Section: Madv Architecturementioning

confidence: 99%

A Morphogenetically Assisted Design Variation Tool

Adler

Yaman

Beal

et al. 2013

AAAI

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The complexity and tight integration of electromechanical systems often makes them "brittle" and hard to modify in response to changing requirements. We aim to remedy this by capturing expert knowledge as functional blueprints, an idea inspired by regulatory processes that occur in natural morphogenesis. We then apply this knowledge in an intelligent design variation tool. When a user modifies a design, our tool uses functional blueprints to modify other components in response, thereby maintaining integration and reducing the need for costly search or constraint solving. In this paper, we refine the functional blueprint concept and discuss practical issues in applying it to electromechanical systems. We then validate our approach with a case study applying our prototype tool to create variants of a miniDroid robot and by empirical evaluation of convergence dynamics of networks of functional blueprints.

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Section: Madv Architecturementioning

confidence: 99%

A Morphogenetically Assisted Design Variation Tool

Adler

Yaman

Beal

et al. 2013

AAAI

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“…Prior development-inspired representations for electromechanical design (e.g., [7,3,6,5,2]) represent topological relations and constraints implicitly, through the geometric simulation of development. This is often computationally expensive, and in many cases results in unintended dependencies or representational commitments imposed by the progress of a design through intermediate forms on its way to a "mature" state where the design can be evaluated.…”

Section: Motivationmentioning

confidence: 99%

“…Example constructions of (a) a 3D rectangle from three Extrudes, (b) linking X+,Y-and W-Y-1-cells with Connect, and (c) four symmetric regions from a corner-anchored AlignedSubspace.operators, we consider a set of five operators based on the set in[2]. These operators and their parameters are:• Extrude(cells,coordinate): For every k-cell (a kdimensional space homeomorphic to the unit ball) in the set cells, extend that cell to create a new orthogonal axis measured by coordinate.• Connect(-cells,+cells,coordinate): For every k-cell in the set -cells, create a (k + 1)-cell measured by coordinate that connects to it from the k-cell in +cells with the most similar values of other coordinates.…”

mentioning

confidence: 99%

Mixed geometric-topological representation for electromechanical design

Beal

Adler

Mostafa

2013

Proceedings of the 15th Annual Conference Companion on Genetic and Evolutionary Computation

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Avoiding unintended representational commitments is a key challenge in generative design. We have developed a mixed geometric-topological representation based on CW-complexes, which represents structure and geometric constraints such that commitments regarding position and layout are latebinding and resolve only during the evaluation of a design instance. Complicated designs can be elaborated into a full representation using a small number of biologically-inspired developmental operators. We illustrate the new representation with a number of examples of electromechanical design. MOTIVATIONA key challenge in generative design is to find representations that allow smooth navigation of the design space. Natural biological organisms, which are remarkably adaptable both as individuals and in evolving populations over time, derive much of their adaptability from the process of morphogenesis [4,8], in which the basic topological structures and relations laid out in these early stages of development then persist throughout development, even as the various body parts and organs assume their full-grown dimensions.Prior development-inspired representations for electromechanical design (e.g., [7, 3, 6, 5, 2]) represent topological relations and constraints implicitly, through the geometric simulation of development. This is often computationally expensive, and in many cases results in unintended dependencies or representational commitments imposed by the progress of a design through intermediate forms on its way to a "mature" state where the design can be evaluated.We propose instead to base a representation on topology and attach geometric parameters and constraints to this model only as they become relevant, creating a "latebinding" geometry that preserves flexibility and symmetry * Sponsored by DARPA under contract W91CRB-11-C-0052; views and conclusions contained in this document are those of the authors and not DARPA or the U.S. Gov't. ACM 978-1-4503-1964-5/13/07. except where explicitly broken and allows constraints and dependent parameters to be specified implicitly. HYBRID REPRESENTATIONWe have developed a hybrid topological-geometric representation in four layers of objects and directed binary relations. The foundation layer is a construct of topological cells, specifying the collection of geometric components making up a design and their attachment and containment relations. We based this on a topological object known as a CW-complex [9], a topological cousin to familiar geometric engineering constructs such as the polygonal mesh and thus a natural fit for representing electromechanical designs.To this topological base, we attach numerical parameters and measurements. In some cases, these parameters represent aspects of geometry, and thereby add constraint to the topology, while in other cases they associate other types of specification information (e.g., material properties). Each parameter's units are specified, though its value is not set at this layer of the representation.The third layer is a collection of ...

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“…Each cell's behaviour is controlled by an internal gene regulatory network [53]. Examples of physical experiments based on the same principles are done in morphogenetic or epigenetic robotics [149][150][151], where the morphology and control system of robots are evolved to fit a certain environment and then physically built. These works explore the causal and programmable link from genotype to phenotype as well as the co-development of body and (natural or artificial) brain.…”

Section: A U T H O R C O P Ymentioning

confidence: 99%

The future of complexity engineering

Frei

Serugendo

2012

Open Engineering

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AbstractComplexity Engineering encompasses a set of approaches to engineering systems which are typically composed of various interacting entities often exhibiting self-* behaviours and emergence. The engineer or designer uses methods that benefit from the findings of complexity science and often considerably differ from the classical engineering approach of “divide and conquer”.This article provides an overview on some very interdisciplinary and innovative research areas and projects in the field of Complexity Engineering, including synthetic biology, chemistry, artificial life, self-healing materials and others. It then classifies the presented work according to five types of nature-inspired technology, namely: (1) using technology to understand nature, (2) nature-inspiration for technology, (3) using technology on natural systems, (4) using biotechnology methods in software engineering, and (5) using technology to model nature. Finally, future trends in Complexity Engineering are indicated and related risks are discussed.

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A manifold operator representation for adaptive design

Cited by 4 publications

References 17 publications

A Morphogenetically Assisted Design Variation Tool

A Morphogenetically Assisted Design Variation Tool

Mixed geometric-topological representation for electromechanical design

The future of complexity engineering

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