Integration of multiple partial point clouds based on estimated parameters in photogrammetry with QR codes

Baba, Keita*; Watanobe, Yutaka*; Nakamura, Keita*; Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki

Proceedings of 29th International Symposium on Artificial Life and Robotics (AROB 2024) (Internet), p.751 - 756, 2024/01

Integration of multiple local point clouds based on estimated parameters in photogrammetry with QR code

Nakamura, Keita*; Baba, Keita*; Watanobe, Yutaka*; Matsumoto, Taku; Hanari, Toshihide; Kawabata, Kuniaki

no journal, , 

This study proposes a method for integrating reconstructed models by partial-to-partial registration using photogrammetry reconstructed models and QR codes. It has been considered difficult to integrate photogrammetry reconstructed models because the scale of each reconstructed model is different each time. In this study, we solve this problem by placing QR codes of known size in the environment for reconstruction and scaling each reconstructed model based on the size of the QR code. To verify this method, we compared the accuracy of the integrated model with that of the reconstructed model from all images. The comparison results show that a tolerance of 20 mm is highly accurate. We consider that this approach will be effective in reducing the time required for mapping using robotic and photogrammetric methods.