Parallelized Iterative Closest Point for Autonomous Aerial Refueling
The Iterative Closest Point algorithm is a widely used approach to aligning the geometry between two 3 dimensional objects. The capability of aligning two geometries in real time on low-cost hardware will enable the creation of new applications in Computer Vision and Graphics. The execution time of many modern approaches are dominated by either the k nearest neighbor search (kNN) or the point alignment phase. This work presents an accelerated alignment variant which utilizes parallelization on a Graphics Processing Unit (GPU) of multiple kNN approaches augmented with a novel Delaunay Traversal to achieve real time estimates.
Advances in Visual Computing. ISVC 2016 (LNCS 10072)
Robinson J., Piekenbrock M., Burchett L., Nykl S., Woolley B., Terzuoli A. (2016) Parallelized Iterative Closest Point for Autonomous Aerial Refueling. In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science, vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_53