CAREER: Morphogenetic Primitives: Self-Organizing Geometry Based on Morphogenesis and Evolutionary Computing

职业：形态发生原语：基于形态发生和进化计算的自组织几何

• 批准号: 0845415
• 负责人: David Breen
• 金额: $ 43.61万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-03-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0845415&HistoricalAwards=false
• 关键词: CAREER; Morphogenetic; Primitives; Self; Organizing

Morphogenetic Primitives: Self-Organizing Geometry Based on Morphogenesis and Evolutionary ComputingDr. David BreenDepartment of Computer ScienceDrexel UniversityIt has been noted that two types of systems exist in the world: 1) systems designed and built by humans to perform a specific job, and 2) biological systems that self-organize to also perform complex tasks without a master plan or overseer directing the actions. The self-organization found in biological systems is a powerful untapped paradigm that, if formulated and exploited, could lead to a superior approach to designing human-made structures. Self-organization algorithms could enable collections of software agents, micro-devices and engineered cells to form into user-defined shapes using only minimal, local information. Developing these algorithms should lead to advances in geometric computer-aided design, tissue engineering, swarm robotics, sensor networks and the custom-design of living cell aggregates.This research project combines and extends concepts from morphogenesis (the cell-level spatial process that produces the structure of an organism), cell aggregation simulation and evolutionary computing in order to produce a new, organic approach to shape generation. Called Morphogenetic Primitives (MPs), this approach captures the fundamental algorithmic constructs of geometric self-organization and harnesses their capabilities within a software framework. MPs are being applied to a number of innovative and important problem-domain areas. The approach creates a new class of self-organizing modeling primitives that may be programmed to ?grow? shapes that meet a specific need while adapting to constraints in the environment. The conceptual framework of MPs is rooted in developmental biology and is based on the multiple biological/physical mechanisms of morphogenesis. Local cell-level interactions aggregate to create high-level shapes and structures. Given the extreme challenges of determining the correct local actions that produce a desired final structure, evolutionary computing techniques are utilized in order to computationally produce the instructions and equations needed for a specific morphogenetic primitive application.

形态发生原语：基于形态发生和进化计算的自组织几何。人们注意到，世界上存在两种类型的系统：1)由人类设计和建造的系统，用于执行特定的工作；2)自组织的生物系统，它也可以在没有总体计划或监督的情况下执行复杂的任务。在生物系统中发现的自组织是一种强大的未被开发的范例，如果被制定和利用，可能会导致设计人造结构的更好方法。自组织算法可以使软件代理、微型设备和工程细胞的集合仅使用最少的本地信息就能形成用户定义的形状。开发这些算法将导致几何计算机辅助设计、组织工程、群体机器人、传感器网络和活细胞聚集体定制设计的进步。这项研究项目结合并扩展了形态发生(产生有机体结构的细胞级空间过程)、细胞聚集模拟和进化计算的概念，以产生一种新的、有机的形状产生方法。这种方法被称为形态发生基元(MPS)，它捕获了几何自组织的基本算法结构，并在软件框架内利用了它们的能力。减贫战略正被应用于一些创新和重要的问题领域。该方法创建了一类新的自组织建模原语，这些原语可以被编程为？增长？在适应环境中的约束的同时满足特定需求的形状。MPS的概念框架植根于发育生物学，并基于形态发生的多种生物学/物理机制。局部细胞级别的相互作用聚集在一起以创建高级别的形状和结构。考虑到确定产生所需最终结构的正确局部动作的极端挑战，进化计算技术被用于计算产生特定形态发生原语应用所需的指令和方程。