基于智能虚拟器官的植物建模关键技术研究
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摘要
虚拟植物是以计算机仿真技术为基础,融合人工智能、植物学和植物生理学等多学科门类的新兴交叉研究领域,是国家数字农业战略规划的重要组成部分,也是农业信息化的核心研究内容之一,具有重大的理论意义与实用价值。目前的研究在实际应用过程中存在一些不足,如功能和结构模型系统耦合性差、参数配置复杂,植物生长规律难以自动发现和提取,基于L系统的模型难以适应复杂的器官功能和结构等。
针对现有研究工作的不足,本文围绕虚拟植物建模方式及关键技术进行研究。论文工作的主要贡献是提出了以智能虚拟器官为基础的虚拟植物系统模型,通过建立智能虚拟器官生长推理过程来模拟器官的生理功能和生长形变,建立基于生长控制器的推理过程来实现虚拟植物的生长发育。主要研究成果包括:
论文通过采集植物生理数据、统计分析和植物生理模糊神经推理等方法自动提取了器官的生长行为规则,获得器官的生理状态参数和生长发育的生理及环境限制条件。采用离散压力流模型和图自动机计算模型实现了智能虚拟器官之间的物质传输与分配。建立了智能虚拟器官的自主化生理过程,实现生理功能。
论文分别采用Bézier曲面和三维重构技术来建立器官三维几何模型。采用Wang Tiles算法来合成纹理,以获得逼真的三维渲染图像。分别通过调整几何参数、三维Morphing和生长函数来实现虚拟器官的生长形变。通过集成的推理过程,计算新生器官获得最大光照的最佳生长角度。
论文构造了生长控制器控制植物生长发育。建立由智能虚拟器官构成的分枝网络,来存储虚拟植物拓扑结构、几何形态和生理信息,并可直接解析出三维可视化图像。生长控制器判断各个器官所处的虚拟环境状态,调用分枝控制器控制分生组织的生长发育。分枝控制器解析分枝规则,输出分枝指令。分枝规则采用二维层次自动机描述和表示,可以人工观测提取,也可以通过图像处理和统计分析来自动提取。
论文在本实验室具有自主知识产权的虚拟植物仿真软件“PlantLab”基础上搭建了仿真平台,以辣椒为仿真对象,研究和模拟其在正常、单向光照、低温、缺水、剪枝等环境条件下的生长发育过程和形态变化,并与实际生长过程的图像和数据进行对比,结果表明本文提出的植物模型能够较为真实、有效地模拟植物的生长发育及形态变化。
As an emerging interdisciplinary field, the research of computer-simulation-based virtual plants combines artificial intelligence, botany and plant physiology as well as other subjects. It is an important part of the national digital agriculture strategic planning, and is the core content of agricultural informationization also, and has great theoretical and practical value. However, there are still some problems and limitations between research and application, such as the function and structure model of poor coupling and difficult to configure complex parameters, being difficult to discover and extract the growth rules automatically, difficult to present complicated functional structure of organs by using the traditional L-system, etc.
This thesis focuses on the research of plant modeling and its key technologies to solve the limitations of existing research. The most important feature of this thesis is that the model based on Intelligent Virtual Organ (IVO) is proposed, IVO implements the growth reasoning process to simulate the physiological function and growth deformation independently, the Growth Controller (GC) implements the intelligent growth reasoning process to achieve the growth and development of the virtual plant. Main contributions are as follows:
First, collecting physiology data of plant, statistical analysis and Fuzzy Neuron Inference of Physiological Process (FNI-PP) have been used to automatically extract the growth behaviors rules of organs, the physiological growth status of organ and the physical and environmental restrictions for development. Discrete pressure-flow model and graph automata have been used to simulate the material transport and distribution and information exchange between IVOs. The autonomous physiological processes of IVOs have been established to achieve physiological functions.
Second, bézier surface and 3D reconstruction technique have been used to create 3D geometric model of organs. Wang Tiles texture synthesis algorithm has been used to obtain 3D rendering vivid images. Adjusting geometrical parameters, 3D Morphing and growth function have been used to implement the growth deformation of virtual organs. IVOs calculate the best angle of new child organ by integrated reasoning process, in which the child organ can maximize light interception.
Third, the Growth Controller (GC) has been established to control the growth and development of the virtual plant. The branching network composed of IVOs has been established, to store the virtual plant topology, geometry and physical information, and can directly be resolved 3D visualization image. GC checks the physiological and virtual environmental status of every organ, calls Branching Controller (BC) to control the growth and development of the meristems. BC analysis the branching rules and exports the branching instructions. The Two Dimensional Hierarchical Automata (2DHA) has been used to say and store the branching rules. The branching rules can be extracted by manually observation, or be extracted automatically by image processing and statistical analysis.
Finally, the model has been implemented on the platform based on the virtual plant simulation software‘PlantLab’, which was developed by our laboratory with indigenous intellectual property rights. Several simulations of cayennes’growth and 3D morphological changes under normal, one-way light, lower temperature, water deficit environment and pruning have been conducted using this simulation platform. The comparison between simulated and real growth data shows that the model can effectively and vividly simulate the growth and development of virtual plant and its deformation.
针对现有研究工作的不足,本文围绕虚拟植物建模方式及关键技术进行研究。论文工作的主要贡献是提出了以智能虚拟器官为基础的虚拟植物系统模型,通过建立智能虚拟器官生长推理过程来模拟器官的生理功能和生长形变,建立基于生长控制器的推理过程来实现虚拟植物的生长发育。主要研究成果包括:
论文通过采集植物生理数据、统计分析和植物生理模糊神经推理等方法自动提取了器官的生长行为规则,获得器官的生理状态参数和生长发育的生理及环境限制条件。采用离散压力流模型和图自动机计算模型实现了智能虚拟器官之间的物质传输与分配。建立了智能虚拟器官的自主化生理过程,实现生理功能。
论文分别采用Bézier曲面和三维重构技术来建立器官三维几何模型。采用Wang Tiles算法来合成纹理,以获得逼真的三维渲染图像。分别通过调整几何参数、三维Morphing和生长函数来实现虚拟器官的生长形变。通过集成的推理过程,计算新生器官获得最大光照的最佳生长角度。
论文构造了生长控制器控制植物生长发育。建立由智能虚拟器官构成的分枝网络,来存储虚拟植物拓扑结构、几何形态和生理信息,并可直接解析出三维可视化图像。生长控制器判断各个器官所处的虚拟环境状态,调用分枝控制器控制分生组织的生长发育。分枝控制器解析分枝规则,输出分枝指令。分枝规则采用二维层次自动机描述和表示,可以人工观测提取,也可以通过图像处理和统计分析来自动提取。
论文在本实验室具有自主知识产权的虚拟植物仿真软件“PlantLab”基础上搭建了仿真平台,以辣椒为仿真对象,研究和模拟其在正常、单向光照、低温、缺水、剪枝等环境条件下的生长发育过程和形态变化,并与实际生长过程的图像和数据进行对比,结果表明本文提出的植物模型能够较为真实、有效地模拟植物的生长发育及形态变化。
As an emerging interdisciplinary field, the research of computer-simulation-based virtual plants combines artificial intelligence, botany and plant physiology as well as other subjects. It is an important part of the national digital agriculture strategic planning, and is the core content of agricultural informationization also, and has great theoretical and practical value. However, there are still some problems and limitations between research and application, such as the function and structure model of poor coupling and difficult to configure complex parameters, being difficult to discover and extract the growth rules automatically, difficult to present complicated functional structure of organs by using the traditional L-system, etc.
This thesis focuses on the research of plant modeling and its key technologies to solve the limitations of existing research. The most important feature of this thesis is that the model based on Intelligent Virtual Organ (IVO) is proposed, IVO implements the growth reasoning process to simulate the physiological function and growth deformation independently, the Growth Controller (GC) implements the intelligent growth reasoning process to achieve the growth and development of the virtual plant. Main contributions are as follows:
First, collecting physiology data of plant, statistical analysis and Fuzzy Neuron Inference of Physiological Process (FNI-PP) have been used to automatically extract the growth behaviors rules of organs, the physiological growth status of organ and the physical and environmental restrictions for development. Discrete pressure-flow model and graph automata have been used to simulate the material transport and distribution and information exchange between IVOs. The autonomous physiological processes of IVOs have been established to achieve physiological functions.
Second, bézier surface and 3D reconstruction technique have been used to create 3D geometric model of organs. Wang Tiles texture synthesis algorithm has been used to obtain 3D rendering vivid images. Adjusting geometrical parameters, 3D Morphing and growth function have been used to implement the growth deformation of virtual organs. IVOs calculate the best angle of new child organ by integrated reasoning process, in which the child organ can maximize light interception.
Third, the Growth Controller (GC) has been established to control the growth and development of the virtual plant. The branching network composed of IVOs has been established, to store the virtual plant topology, geometry and physical information, and can directly be resolved 3D visualization image. GC checks the physiological and virtual environmental status of every organ, calls Branching Controller (BC) to control the growth and development of the meristems. BC analysis the branching rules and exports the branching instructions. The Two Dimensional Hierarchical Automata (2DHA) has been used to say and store the branching rules. The branching rules can be extracted by manually observation, or be extracted automatically by image processing and statistical analysis.
Finally, the model has been implemented on the platform based on the virtual plant simulation software‘PlantLab’, which was developed by our laboratory with indigenous intellectual property rights. Several simulations of cayennes’growth and 3D morphological changes under normal, one-way light, lower temperature, water deficit environment and pruning have been conducted using this simulation platform. The comparison between simulated and real growth data shows that the model can effectively and vividly simulate the growth and development of virtual plant and its deformation.
引文
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[2] Martineau Y, Saugier B. Paradoxical behaviour of a process-based model of plant succession [J]. Comptes Rendus Biologies 2006;329(1):21-30.
[3] Renton M, Kaitaniemi P, Hanan J. Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function [J]. Ecological Modelling 2005;184(2-4):277-98.
[4] Gao F, Wang CZ, Wei CH, Li Y. A branched-chain aminotransferase may regulate hormone levels by affecting KNOX genes in plants [J]. Planta 2009;230(4):611-23.
[5] Coleman HD, Samuels AL, Guy RD, Mansfield SD. Perturbed Lignification Impacts Tree Growth in Hybrid Poplar-A Function of Sink Strength, Vascular Integrity, and Photosynthetic Assimilation [J]. Plant Physiology 2008;148(3):1229-37.
[6] Vos J, Marcelis LFM, Evers JB. Functional-structural plant modelling in crop production[C]. Workshop on Functional-Structural Plant Modelling in Crop Production, Wageningen, NETHERLANDS: 2006; 2006:1-12.
[7] Ren MX, Zhang QG. The relative generality of plant invasion mechanisms and predicting future invasive plants[J]. Weed Research, 2009;49(5):449-60.
[8] Room PM, Maillette L, Hanan JS. Module and Metamer Dynamics and Virtual Plants[J]. Advances in Ecological Research, 1994,25:105-57.
[9]杨娟.基于NURBS曲面的棉花器官建模[J].计算机工程与应用,2005:185-188.
[10] W.T. Reeves, R.Blau. Approximate and probabilististic algorithms for shading and rending structured particle system[J]. Computer Graphics. 1985.19(3):313-322.
[11] A.Lindenmayer. Mathematical models for cellular interaction in development[J], PartsⅠand PartsⅡ. Journal of Theoretical Biology. 1968, 19:280-315.
[12] P. Prusinkiewicz, J. Hanan. Visualization of botanical structures and process using parametric L systems[J]. Scientific Visualization and Graphics simulation, 1990:193-201.
[13] P. Prusinkiewicz, J. Hannan. Lindenmayer Systems, fractals, and plants[M]. New York:Springer-Verlag, 1990:25-30.
[14] P. Prusinkiewicz, M. Hammel. L-system: From the theory to visual models of plants[C]. Presented at Proceedings of the 2nd CSIRO Symposium on Computational Challenges in LifeSciences 1996:113-146.
[15] P. Prusinkiewicz, A. Lindenmayer. The Algorithmic Beauty of Plants [M]. New York:Springer, Berlin Heidelberg, 1990.
[16] Prusinkiewicz. A look at the visual modeling of plant using L-system[J]. Agronomic, 1990, 211-224.
[17] P. Prusinkiewicz, M. Hammel, E. Mjolsness. Animation of plant development[J]. Computer Graphics, 1993, 27 (3): 351-360.
[18] Mech, P. Prusinkiewicz. Visual models of plants interacting with their environment[J]. Computer Graphics, 1996, 30:397-410.
[19] P. Prusinkiewicz. L-Studio. http://algorithmicbotany.org/lstudio/whatis.html[EB/OL]
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