There is a typo in the text of the Problem/Exercise you posted which might confuse
but probably its trivial for most
It should say:
Calculate the vector
$$w=v-<u_{1},v>u_{1}+<u_{2},v>u_{2}$$.
The index 2 has been forgotten in the original text after the last Inner product
in the expression for $w$
Other than that its exactly what poster Jose already said.
The vector w is orthogonal to both vectors $u_{1},u_{2}$(in fact orthogonal to the subspace spanned by $u_{1},u_{2}$) and you have
nothing more to do than to normalize w in order to make your system orthonormal.
In case you have troubles or feel confusing ,the notion of orthogonality
for vectors and how to check it
Consider the following facts/steps.
The vectors $u1,u2$ are normalized and orthogonal to one another.
Note that the vector spaces you consider when you ask for orthogonality are usualy
spaces where the norm is defined via an Inner-Product(for real numbers as scalars this means symmetric,postive definite bilinearform) in the following sense
$$||v||:=<v,v>^{\frac{1}{2}}$$
To check if 2 vectors x,y are orthogonal you have to check for
$<x,y>=0$.
First
If a vector v is projected on a normalized vector u by
$P(v)=<u,v>u$ ,the vector $v-P(v)$ will be orthogonal on u.
This can be easily verified by straightforward calculation checking orthogonality condition for
$x=v-P(v)$ and $y=u$
Second
If a vector w is orthogonal to the unit vectors u1,u2 then w is orthogonal to all
vectors spanned by these.
Again this just straigth forward calculation expressing an arbitrary vector b
of $span\{u_1,u_2\}$ as a Linearcombination of $u_{1},u_{2}$ and using inner product properties.
Last thing important to know is that vectors which are pairwise orthogonal to one another
are linear independent.
When you do these calculations just keep in mind the symmetry and linearity properties
of the Inner product(<,>) and how the Inner product and Norm of your space are related and everything works out smoothly.