Additive Manufacturing (AM) is transforming construction by enabling autonomous, large-scale building. Most existing research focuses on gantry systems and ground robots, which face limitations such as heavy infrastructure, heavy machinery, and restricted workspace. This thesis explores Aerial Additive Manufacturing (AAM) using unmanned aerial Vehicles (UAVs) as mobile builders that deposit material layer by layer. Despite its potential, this approach introduces a distinct set of challenges, including constrained payload capacities, the need for precise manipulation, and the complexity of coordinating multi-agent systems. To address these, a chunk-based aerial 3D printing framework is proposed, covering planning, execution, and coordinated UAV control. A key contribution is a mesh decomposition algorithm that splits structures into printable chunks, enabling balanced task distribution and parallel execution while respecting structural constraints. An offset-free Model Predictive Control (MPC) strategy enhances aerial printing by compensating for ground effects, UAV dynamic asymmetries, and varying payloads, improving both stability and precision. The framework is validated in simulation using Gazebo and in a mockup experiment with a real UAV performing virtual deposition. For full validation, a custom hexacopter with a foam extrusion system demonstrates controlled, precise material deposition. The framework is also extended to support simultaneous multi-UAV deployment, where coordination is guided by structural dependencies among the chunks. Task allocation is performed dynamically, prioritizing critical components to prevent bottlenecks and ensure a smooth workflow, while also accounting for the probabilistic likelihood of conflicts between assignments. Finally, conflict resolution is achieved by minimizing the extent of velocity adjustments required to maintain safe, collision-free operation. This allows UAVs to operate concurrently with minimal delays, thereby improving overall efficiency and productivity in aerial construction. In conclusion, this thesis advances AAM further by introducing a chunk-based planning and coordination framework and laying the foundation for the realization of collaborative aerial autonomous construction.