  Turbulence is a complex nonlinear and multi-scale phenomenon. Although the
fundamental underlying Navier-Stokes equations have been known for two
centuries, it remains extremely challenging to extract from them the
statistical properties of turbulence. Therefore, for practical purpose, a
sustained effort has been devoted to obtaining some effective description of
turbulence, that we may call turbulence modelling, or statistical theory of
turbulence. In this respect, the Renormalisation Group (RG) appears as a tool
of choice, since it is precisely designed to provide effective theories from
fundamental equations by performing in a systematic way the average over
fluctuations. However, for Navier-Stokes turbulence, a suitable framework for
the RG, allowing in particular for non-perturbative approximations, have been
missing, which has thwarted for long RG applications. This framework is
provided by the modern formulation of the RG called functional renormalisation
group. The use of the FRG has rooted important progress in the theoretical
understanding of homogeneous and isotropic turbulence. The major one is the
rigorous derivation, from the Navier-Stokes equations, of an analytical
expression for any Eulerian multi-point multi-time correlation function, which
is exact in the limit of large wavenumbers. We propose in this {\it JFM
Perspectives} a survey of the FRG method for turbulence. We provide a basic
introduction to the FRG and emphasise how the field-theoretical framework
allows one to systematically and profoundly exploit the symmetries. We then
show that the FRG enables one to describe turbulence forced at large scale,
which was not accessible by perturbative means. We expound the derivation of
the spatio-temporal behaviour of $n$-point correlation functions, and largely
illustrate these results through the analysis of data from experiments and
direct numerical simulations.
