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Abstract Aiming at the shortcomings of traditional point cloud registration algorithms, a point cloud initial alignment method based on the differential evolution algorithm is proposed. By designing an appropriate fitness… Click to show full abstract
Abstract Aiming at the shortcomings of traditional point cloud registration algorithms, a point cloud initial alignment method based on the differential evolution algorithm is proposed. By designing an appropriate fitness function and selecting a proper evolution strategy, the probability and speed of finding the globally optimal solution are improved. Finally, the point to plane iterative closest point is used to complete the precise registration. Experimental results prove that the speed and robustness of the algorithm put forward here are improved.
Journal Title: Optik
Year Published: 2021
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