Parallelization of Scan Matching for Robotic 3D Mapping

Abstract — Robotic 3D Mapping of environments is computationally expensive, since 3D scanners sample the environment with many data points. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper extends our solution to the 3D mapping problem by parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics task with on-board means. Index Terms — 3D scan matching, Iterative Closest Point Algorithm