Image-Goal Navigation Algorithm using Viewpoint Estimation

This paper tackles the image-goal navigation problem, in which a robot needs to find a goal pose based on the target image. The proposed algorithm estimates the geometric information between the target pose and the current pose of the robot. Using the estimated geometric information, the navigation policy predicts the most appropriate actions to reach the target pose. We evaluated our method using the Habitat simulator with the Gibson dataset, which provides photo-realistic indoor environments. The experimental results show that adding an ability to estimate the geometric information helps the agent find the target pose much more successfully and time-efficiently. Furthermore, we investigate how this estimation ability affects navigation performances through various experiments.