Autonomous Flights Through Image-Defined Paths

This paper addresses the problem of autonomous quadrotor navigation through a previously-mapped indoor area. In particular, we focus on the case where a user walks through a building and collects images. Subsequently, a visual map of the area, represented as a graph of linked images, is constructed and used for automatically determining visual paths (i.e., sequences of images connecting the start to the end image locations specified by the user). The quadrotor follows the desired path by iteratively (i) determining the desired motion to the next reference frame, (ii) controlling its roll, pitch, yaw-rate, and thrust, and (iii) appropriately switching to a new reference image. For motion estimation and reference-image switching, we concurrently employ the results of the 2pt and the 5pt RANSAC to distinguish and deal with both cases of sufficient and insufficient baseline (e.g., rotation in place). The accuracy and robustness of our algorithm are evaluated experimentally on two quadrotors navigating along lengthy corridors, and through tight spaces inside a building and in the presence of dynamic obstacles (e.g., people walking).