2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
ABSTRACT: The most widely used methods for toolpath planning in fused deposition 3D printing slice the input model into successive 2D layers in order to construct the toolpath. Unfortunately slicing-based methods can incur a substantial amount of wasted motion (i.e., the extruder is moving while not printing), particularly when features of the model are spatially separated. In recent work we have introduced a new paradigm that constructs the toolpath in 3D and prints local features to minimize wasted motion. Our algorithm is based on a local search and we have demonstrated substantial improvements in the efficiency of the resulting toolpaths. Our approach is amenable to incorporating physical constraints of the 3D printing process, and, in this paper we extend our approach to incorporate kinematic properties into toolpath optimization. With an accurate kinematic model of the extruder, our algorithm is able to model the real-world fabrication time of the model with a high degree of accuracy. To our knowledge, this toolpath optimization algorithm is the first to encode real-world fabrication time as the objective function. We demonstrate the real-world improvement in fabrication time that is possible with our algorithm on a benchmark of almost 600 models. We find improvement in nearly every toolpath generated for our benchmark set (with a mean of 3.2%), but substantially larger improvements for some models. To rationalize these results, we introduce a metric for model characterization that we call “oriented compactness” and show that it correlates positively with our observations. We believe this metric can be an important tool in the setup of fabrication (e.g., by guiding an orientation search of the model).