CPS: Medium: Accurate and Efficient Collective Additive Manufacturing by Mobile Robots

民用基础设施老化是一个严重影响人们日常生活的世界性问题，因此，创新更高效、更经济的民用结构维修和施工方法显得尤为重要。添加制造或3D打印为满足这一迫切需求提供了一种很有前途的方法。然而，目前几乎所有的添加剂制造方法都依赖于基于门架的系统，该系统只能在刚性框架内建造结构，从而限制了印刷速度和规模，从而阻碍了它们在维护和施工中的使用。该奖项支持建立集体加法制造的基础研究，这是一种基于机器人的大规模3D打印的新方法。集体加法制造利用一组自主移动机器人联合打印大型3D结构。这项研究的结果将在民用基础设施维护和建设、灾后应对和外星建设方面具有潜在的广泛应用。该项目基于一种涉及机器人学、人工智能、控制理论和动力系统的融合研究方法，最终形成正式和非正式的学习活动，以扩大未被充分代表的群体在工程中的参与。集体添加剂制造设想使用移动机器人团队来克服现有基于门架的添加剂制造的主要限制，包括规模小和印刷速度慢。为了充分释放集体加法制造的潜力，必须突破几个科学界限，确保多个移动机器人的最佳部署，这些机器人根据工程设计的虚拟设计打印大型结构。这项研究将填补机器人定位、控制和协调方面的关键知识空白，实现一个有意识地、主动地修改环境以成功完成打印任务的机器人团队。这一跨学科的研究计划将沿着三个方向展开：用于规划和本地化的人工智能，用于适应印刷干扰和基材变化的模型预测控制，以及用于获得稳定的集体动态的分布式控制。理论进步将与实验研究一起进行，以展示集体添加剂制造在真实世界环境中准确和高效打印大型结构的潜力。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Aging civil infrastructure is a critical worldwide problem that affects daily life, making it important to innovate more efficient and economical repair and construction methods for civil structures. Additive manufacturing, or 3D printing, offers a promising way to fulfill this compelling need. However, almost all current additive manufacturing methods rely on gantry-based systems that can only build structures within rigid frames, thereby restricting printing speed and scale, thus hindering their use in maintenance and construction. This award supports fundamental research to establish collective additive manufacturing, a novel robotics-based approach for large-scale 3D printing. Collective additive manufacturing uses a team of autonomous mobile robots to jointly print large-scale 3D structures. The results of the research will have a potentially wide range of applications in civil infrastructure maintenance and construction, to post-disaster response and extraterrestrial construction. The project is based on a convergent research approach involving robotics, artificial intelligence, control theory, and dynamical systems, which culminates in formal and informal learning activities to broaden participation of underrepresented groups in engineering.Collective additive manufacturing envisions the use of teams of mobile robots to overcome key limitations of existing gantry-based additive manufacturing, including its small scale and slow printing speed. To unleash the full potential of collective additive manufacturing, several scientific boundaries must be pushed, ensuring optimal deployment of multiple mobile robots that print large structures according to an engineered, virtual design. This research will fill critical knowledge gaps in robotic localization, control, and coordination, to realize a robotic team that intentionally and actively modifies its surroundings to successfully complete its printing task. This interdisciplinary research program will unfold along three thrusts: artificial intelligence for planning and localization, model predictive control to adapt to printing disturbances and substrate variations, and distributed control to elicit stable collective dynamics. Theoretical advancements will proceed alongside with experimental research toward demonstrating the potential of collective additive manufacturing to accurately and efficiently print large structures in real-world settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.