Based on precisely matching of point cloud, this paper proposes an improved ICP algorithm.
针对点云精确匹配，提出一种改进的ICP算法。
When the ICP algorithm combines with RANSAC algorithm, the registration is high-speed and robust.
论文把RANSAC粗配准算法与ICP精确配准算法相结合，具有较高的收敛速度和鲁棒性。
But the convergence speed is still slow and the ICP algorithm may not converge to a global minimum.
但ICP配准算法的收敛速度较慢，且不能保证收敛到全局最优点。
Finally, by using ICP algorithm to modify the former result, the optimal registration can be achieved.
最后采用ICP算法对点云初配结果进行优化，实现点云精确配准。
Through point cloud data acquired from the building, the course of registration based ICP algorithm is provided.
通过建筑物三维激光扫描数据的采集，对基于ICP算法的点云数据配准过程进行了详细地分析。
Nowadays, the most popular registration algorithm is the ICP algorithm, which utilizes iterative method to approach the best result.
目前，应用最普遍的数据配准算法是最近点迭代（ICP）算法，它采用迭代方式逐渐逼近最佳结果。
The method solves the problem of local minima of ICP algorithm, and the described method is also useful in the field of comparative analysis for precision measurement.
采用两步法配准克服了标准ICP算法难以解决的局部最小问题，本算法也可广泛应用于精密测量时测量结果的比较分析。
The working mechanism of classical ICP algorithm is deeply studied, and its advantages and limits are analyzed. Registration based on angular-invariant is then proposed.
深入研究了经典ICP算法的工作原理，分析了ICP算法的优点和局限性，进而提出了基于角特征不变量的配准算法。
The working mechanism of classical ICP algorithm is deeply studied, and its advantages and limits are analyzed. Registration based on angular-invariant is then proposed.
深入研究了经典ICP算法的工作原理，分析了ICP算法的优点和局限性，进而提出了基于角特征不变量的配准算法。
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