Reconstruction stack shape detection for robot palletizing

Huiqiang Yu; Yongyi He; Qian Wen

doi:10.1117/12.2659089

23 November 2022 Reconstruction stack shape detection for robot palletizing

Huiqiang Yu, Yongyi He, Qian Wen

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 1245419 (2022) https://doi.org/10.1117/12.2659089
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

As the robot enters the carriage or container for stacking, it is inevitable to develop a reasonable stack shape detection method to timely find the wrong situations such as stacking boxes tipping and non-conforming to packing constraints, and timely correct them to ensure the smooth stacking. Therefore, a high precision stack detection method based on three-dimensional reconstruction of solid state lidar (Livox Mid-70) is designed. The actual palletizing type point cloud was obtained by laser SLAM reconstruction. Combined with the theoretical palletizing type point cloud result, the overall root mean square error of the actual reconstructed palletizing type and the theoretical planned palletizing type was calculated by point cloud registration technology, and the palletizing effect was tested. The point cloud registration experiment is carried out by using the point cloud obtained by simulation and the point cloud extracted by planning stack shape. The results show that the stack shape detection method can meet the actual requirements in detection accuracy and detection time, and verify the effectiveness of the method.

Citation Download Citation

Huiqiang Yu, Yongyi He, and Qian Wen "Reconstruction stack shape detection for robot palletizing", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 1245419 (23 November 2022); https://doi.org/10.1117/12.2659089

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