利用非线性优化函数需要提供一个初始值，并且初始值要尽量接近真值，以免陷

The use of a nonlinear optimization function needs to provide an initial value, and the initial value should be as close as possible to the true value, so as not to fall into the local extreme value. Because of the relative transformation involved in three-dimensional space, the initial value obtained by manual measurement is unreliable and the error is large. By constructing a linear equation to solve, it can provide an initial value for optimization.

Using nonlinear optimization functions requires providing an initial value, and the initial value should be as close to the true value as possible to avoid falling into the local extremum. Because of the relative transformation of three-dimensional space, the initial value obtained by manual measurement is unreliable and the error is large. By constructing linear equation solving, it is possible to provide an initial value for optimization.

Using nonlinear optimization function needs to provide an initial value, and the initial value should be as close to the true value as possible to avoid falling into local extreme value. Due to the relative transformation of three-dimensional space, the initial value obtained by manual measurement is unreliable and the error is large. By constructing a linear equation to solve, it can provide an initial value for optimization.<br>