Aerial 3D printing is a pioneering technology yet in its conceptual stage that combines frontiers of 3D printing and Unmanned aerial vehicles (UAVs) aiming to construct large-scale structures in remote and hard-to-reach locations autonomously. The envisioned technology will enable a paradigm shift in the construction and manufacturing industries by utilizing UAVs as precision flying construction workers. However, the limited payload-carrying capacity of the UAVs, along with the intricate dexterity required for manipulation and planning, imposes a formidable barrier to overcome. Aiming to surpass these issues, a novel aerial decomposition-based and scheduling 3D printing framework is presented in this article, which considers a near-optimal decomposition of the original 3D shape of the model into smaller, more manageable sub-parts called chunks. This is achieved by searching for planar cuts based on a heuristic function incorporating necessary constraints associated with the interconnectivity between subparts, while avoiding any possibility of collision between the UAV’s extruder and generated chunks. Additionally, an autonomous task allocation framework is presented, which determines a priority-based sequence to assign each printable chunk to a UAV for manufacturing. The efficacy of the proposed framework is demonstrated using the physics-based Gazebo simulation engine, where various primitive CAD-based aerial 3D constructions are established, accounting for the nonlinear UAVs dynamics, associated motion planning and reactive navigation through Model predictive control.

空中 3D 打印是一项尚处于概念阶段的开创性技术，它结合了 3D 打印和无人机 (UAV) 的前沿技术，旨在在偏远和难以到达的地点自主建造大型结构。设想的技术将利用无人机作为精确飞行的建筑工人，从而实现建筑和制造业的范式转变。然而，无人机有限的有效载荷承载能力，以及操纵和规划所需的复杂灵活性，构成了需要克服的巨大障碍。为了解决这些问题，本文提出了一种新颖的基于空中分解和调度的 3D 打印框架，该框架考虑将模型的原始 3D 形状近乎最优地分解为更小、更易于管理的子部分（称为块）。这是通过基于启发式函数搜索平面切割来实现的，该启发式函数结合了与子部件之间互连性相关的必要约束，同时避免了无人机的挤出机和生成的块之间发生任何碰撞的可能性。此外，还提出了一个自主任务分配框架，它确定基于优先级的顺序，将每个可打印块分配给无人机进行制造。使用基于物理的 Gazebo 仿真引擎证明了所提出框架的有效性，其中建立了各种基于 CAD 的原始航空 3D 结构，通过模型预测控制考虑了非线性无人机动力学、相关运动规划和反应导航。