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A 3D Reconstruction Method Based on the Combination of the ICP and Artificial Potential Field Algorithm

机译:一种基于ICP和人工潜在场算法组合的3D重构方法

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摘要

For real-time and accurate three-dimensional (3D) reconstruction during autonomous mobile robot navigation, a method based on the combination of iterative closest points (ICP) and artificial potential field algorithm (APF) is proposed. In real-time path planning, the mobile robot uses the artificial potential field method to obtain the environment point-cloud image by Kinect. Then, the combination of the improved ICP method and the initial transformation matrix is applied to complete the 3D reconstruction. The experimental results show that the proposed algorithm is more efficient than normal distributions transform (NDT) and the traditional three-dimensional ICP method.
机译:对于自主移动机器人导航期间的实时和准确的三维(3D)重建,提出了一种基于迭代最接近点(ICP)和人工势场算法(APF)的组合的方法。在实时路径规划中,移动机器人使用人工潜在的现场方法来通过Kinect获得环境点云图像。然后,应用改进的ICP方法和初始变换矩阵的组合来完成3D重建。实验结果表明,该算法比正常分布(NDT)和传统的三维ICP方法更有效。

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