A Heuristic Scaling Strategy for Multi-Robot Cooperative Three-Dimensional Printing
A Heuristic Scaling Strategy for Multi-Robot Cooperative Three-Dimensional Printing
复制标题
多机器人协作三维打印的启发式缩放策略
DOI：
10.1115/1.4045143
复制
发表时间：
2020
影响因子：
3.1
通讯作者：
Zhou, Wenchao
中科院分区：
文献类型：
--
作者：
Poudel, Laxmi;Blair, Chandler;McPherson, Jace;Sha, Zhenghui;Zhou, Wenchao
虽然三维（3D）打印在过去几十年中取得了长足的进步，但由于其在打印尺寸和打印速度方面缺乏可扩展性，它仍然落后于主流制造业。协同3D打印（C3DP）是一种新兴技术，其通过使一群携带打印头的移动的机器人一起协作完成单个打印作业来有望缓解这两个问题。在我们以前的工作中，我们已经开发了一种基于块的打印策略，以实现与两台熔融沉积成型（FDM）移动的3D打印机的协作3D打印，这使得它们中的每一个都可以一次打印一个块，而不会干扰另一个和打印部件。在本文中，我们提出了一种新的方法，在离散化的连续3D打印过程中，所需的部分被离散成块，导致多阶段的3D打印过程。此外，这项研究的主要贡献是第一个工作缩放策略的合作3D打印的基础上简单的印刷术，称为可扩展的并行阵列的机器人3DP（SPAR 3），它使许多移动的3D打印机一起工作，以减少总的打印时间为大的打印。为了评估打印策略的性能，开发了一个框架的基础上有向依赖树（DDT），它提供了一个数学和图形的依赖关系和打印任务的顺序描述。基于图的框架可用于估计给定打印策略的总打印时间。沿着的时间评估指标，开发的框架为我们提供了一个数学表示的几何约束，时空动态的，需要得到满足，以实现无碰撞打印的任何C3DP策略。基于DDT的评估框架，然后用来评估拟议的SPAR 3战略。结果验证了SPAR3作为一种无碰撞策略，与传统的单打印头3D打印相比，可以显着缩短打印时间（对于演示示例，使用16个机器人的速度约为11倍）。
While three-dimensional (3D) printing has been making significant strides over the past decades, it still trails behind mainstream manufacturing due to its lack of scalability in both print size and print speed. Cooperative 3D printing (C3DP) is an emerging technology that holds the promise to mitigate both of these issues by having a swarm of printhead-carrying mobile robots working together to finish a single print job cooperatively. In our previous work, we have developed a chunk-based printing strategy to enable the cooperative 3D printing with two fused deposition modeling (FDM) mobile 3D printers, which allows each of them to print one chunk at a time without interfering with the other and the printed part. In this paper, we present a novel method in discretizing the continuous 3D printing process, where the desired part is discretized into chunks, resulting in multi-stage 3D printing process. In addition, the key contribution of this study is the first working scaling strategy for cooperative 3D printing based on simple heuristics, called scalable parallel arrays of robots for 3DP (SPAR3), which enables many mobile 3D printers to work together to reduce the total printing time for large prints. In order to evaluate the performance of the printing strategy, a framework is developed based on directed dependency tree (DDT), which provides a mathematical and graphical description of dependency relationships and sequence of printing tasks. The graph-based framework can be used to estimate the total print time for a given print strategy. Along with the time evaluation metric, the developed framework provides us with a mathematical representation of geometric constraints that are temporospatially dynamic and need to be satisfied in order to achieve collision-free printing for any C3DP strategy. The DDT-based evaluation framework is then used to evaluate the proposed SPAR3 strategy. The results validate the SPAR3 as a collision-free strategy that can significantly shorten the printing time (about 11 times faster with 16 robots for the demonstrated examples) in comparison with the traditional 3D printing with single printhead.
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