Question about the imitation learning strategy in the paper

[YESAndy]

Hi Yicong,

I realized that the imitation learning loss you used in the code base is essentially the cross entropy loss between the predicted action and the oracle action which is obtained by selecting the closest waypoint to the goal. However, this oracle action might not be optimal because sometimes the closest waypoint may not be on the ground truth path (reference path in the dataset). like the following pic,

It is likely to cause the agent to loop around the area.

As the waypoint predictor shows very good results, I wonder if you can comment on how the waypoint predictor manages to avoid the above issue.

Many thanks! Andy