Pretraining for VLN Tasks Two forms of data sam-

ples - in-domain and generic - are used in pretraining prior
to conducting VLN tasks.
In-domain data samples have
been sourced from image-caption pairs from online rental
listings [13] and other VLN tasks [43].
In-domain sam-
ples have also been generated by augmenting or reusing in-
task data [9, 17, 14, 15, 31]. Generic samples from large-
scale datasets designed for other Vision-Language tasks
have been sourced to improve generalisation in transformer-
based VLN agents.
[28] conduct large-scale pretraining
with 3.3M image-text pairs from Conceptual Captions [32]
and [30] initialise a framework with weights trained on four
out-of-domain datasets.
In contrast our training strategy
employs datasets with a few thousand samples of in-domain
data derived from resources where additional samples are
available at low cost.
APriorityMapforVision-and-LanguageNavigation withTrajectoryPlansandFeature-LocationCues