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

土木基础设施老化是影响日常生活的重要世界性问题，因此创新更高效、更经济的土木结构修复和施工方法变得非常重要。增材制造或3D打印为满足这一迫切需求提供了一种有希望的方式。然而，目前几乎所有的增材制造方法都依赖于基于龙门架的系统，这些系统只能在刚性框架内构建结构，从而限制了打印速度和规模，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增材制造的基础研究，这是一种基于机器人的新型大规模3D打印方法。集体增材制造使用一组自主移动机器人共同打印大型3D结构。研究结果将在民用基础设施的维护和建设、灾后响应和地外建设等方面具有广泛的应用前景。该项目以融合研究方法为基础，涉及机器人、人工智能、控制理论和动力系统，最终通过正式和非正式的学习活动扩大工程中代表性不足群体的参与。集体增材制造设想使用移动机器人团队来克服现有基于龙门架的增材制造的关键限制，包括规模小和打印速度慢。为了释放集体增材制造的全部潜力，必须突破几个科学界限，确保根据工程虚拟设计打印大型结构的多个移动机器人的最佳部署。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，实现机器人团队有意识地、主动地修改其周围环境以成功完成其打印任务。这个跨学科的研究项目将沿着三个方向展开：用于规划和定位的人工智能，用于适应印刷干扰和基材变化的模型预测控制，以及用于引发稳定集体动态的分布式控制。理论进步将与实验研究一起进行，以证明集体增材制造在现实环境中准确有效地打印大型结构的潜力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.