Flexible Multi-DoF Aerial 3D Printing Supported with Automated Optimal Chunking
Marios-Nektarios Stamatopoulos, Avijit Banerjee, George, Nikolakopoulos

TL;DR
This paper introduces a novel autonomous multi-UAV framework for large-scale 3D printing that divides complex models into manageable chunks, optimally allocates them, and enables collaborative aerial construction in challenging environments.
Contribution
It presents a new chunk-based distributed 3D printing framework with algorithms for mesh partitioning, chunk allocation, and multi-UAV coordination, advancing autonomous aerial manufacturing capabilities.
Findings
Framework successfully partitions models into planar chunks.
Simulations demonstrate effective multi-UAV collaborative printing.
Optimized chunk allocation improves printing efficiency.
Abstract
The future of 3D printing utilizing unmanned aerial vehicles (UAVs) presents a promising capability to revolutionize manufacturing and to enable the creation of large-scale structures in remote and hard- to-reach areas e.g. in other planetary systems. Nevertheless, the limited payload capacity of UAVs and the complexity in the 3D printing of large objects pose significant challenges. In this article we propose a novel chunk-based framework for distributed 3D printing using UAVs that sets the basis for a fully collaborative aerial 3D printing of challenging structures. The presented framework, through a novel proposed optimisation process, is able to divide the 3D model to be printed into small, manageable chunks and to assign them to a UAV for partial printing of the assigned chunk, in a fully autonomous approach. Thus, we establish the algorithms for chunk division, allocation, and…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Robotic Path Planning Algorithms · 3D Surveying and Cultural Heritage
