6533b838fe1ef96bd12a4f91

RESEARCH PRODUCT

GPU-Based Optimisation of 3D Sensor Placement Considering Redundancy, Range and Field of View

Joacim DybedalGeir Hovland

subject

0303 health sciences030306 microbiologyComputer scienceVolume (computing)020207 software engineeringField of view02 engineering and technology3d sensor03 medical and health sciencesRange (mathematics)CUDAComputer engineering0202 electrical engineering electronic engineering information engineeringRedundancy (engineering)Fraction (mathematics)General-purpose computing on graphics processing units

description

This paper presents a novel and efficient solution for the 3D sensor placement problem based on GPU programming and massive parallelisation. Compared to prior art using gradient-search and mixed-integer based approaches, the method presented in this paper returns optimal or good results in a fraction of the time compared to previous approaches. The presented method allows for redundancy, i.e. requiring selected sub-volumes to be covered by at least n sensors. The presented results are for 3D sensors which have a visible volume represented by cones, but the method can easily be extended to work with sensors having other range and field of view shapes, such as 2D cameras and lidars.

yearjournalcountryeditionlanguage
2020-11-092020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA)
https://doi.org/10.1109/iciea48937.2020.9248170