对于神经网络来说，我们已经习惯了层状网络的思维：数据进来，经过第一层，然后第二层，第三层，最后输出结果。这个过程很像流水线，每一步都是离散的。

做机器人逆运动学（IK）的时候，你迟早会遇到矩阵指数和对数这些东西。为什么呢？因为计算三维旋转的误差，不能简单地用欧氏距离那一套，那只对位置有效。旋转得用另一套方法——你需要算两个旋转矩阵之间的差异，这就涉及到矩阵对数了。

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