abstract: Collective navigation occurs when individuals coordinate their movements to travel as a group to some destination. One potential advantage of collective navigation is to improve the efficiency of migration, for example through the presence of more knowledgeable individuals that guide naive members ("leader-follower behaviour") or through the averaging out of individual uncertainty ("many wrongs"). In this talk I will describe a number of individual and continuous approaches for modelling collective navigation. Individual based models are predicated on a velocity-jump random walk model, but where individuals supplement their own inherent guidance information with information acquired from other group members. Continuous models can be formulated in the form of macroscopic PDE systems. We will show the conditions under which group information can benefit migration, particularly in order to navigate through areas with negligible guidance information. We will consider applications in a number of examples, from the migrations of cells to turtles and whales.