Efficient scene encoding for programmable matter self-reconfiguration algorithms

Thadeu Tucci, Benoît Piranda, J. Bourgeois
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引用次数: 15

Abstract

Programmable matter can be seen as a huge modular robot in which each module can communicate to its connected neighbors and work all together to achieve a common goal, more likely changing the shape of the whole robot. However, when the number of modules increases, the memory used in each module to store the target shape or the computation time to recreate this shape increases too. This article studies different approaches to describe the shape of any object for huge modular robots. The use of a good method for coding scene is a critical aspect that can reduce the memory, the time of transfer and the energy used in many distributed algorithms like self-reconfiguration. This paper proposes a method called Constructive Solid Geometry for Programmable Matter (CSG4PM), a compact description of an object and all the associated algorithms pre-processing and runtime. CSG4PM is compared to three existing solutions to describe a scene.
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可编程物质自重构算法的高效场景编码
可编程物质可以被看作是一个巨大的模块化机器人,其中每个模块都可以与连接的相邻模块通信,并一起工作以实现一个共同的目标,更有可能改变整个机器人的形状。但是,当模块数量增加时,每个模块中用于存储目标形状的内存或重新创建该形状的计算时间也会增加。本文研究了描述大型模块化机器人任意物体形状的不同方法。在自重构等分布式算法中,使用一种好的场景编码方法是减少内存、传输时间和能量消耗的关键。本文提出了一种称为可编程物质构造立体几何(CSG4PM)的方法,该方法是一个对象的紧凑描述以及所有相关的预处理和运行算法。将CSG4PM与现有的三种描述场景的解决方案进行比较。
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