Position and Orientation of an Aerial Vehicle Through Chained, Vision-Based Pose Reconstruction

Abstract

While a Global Positioning System (GPS) is the most widely used sensor modality for aircraft navigation, researchers have been motivated to investigate other navigational sensor modalities because of the desire to operate in GPS denied environments. Due to advances in computer vision and control theory, monocular camera systems have received growing interest as an alternative/collaborative sensor to GPS systems. Cameras can act as navigational sensors by detecting and tracking feature points in an image. One limiting factor in this method is the current inability to relate feature points as they enter and leave the camera …eld of view. The contribution of this paper is a new vision-based state estimation method that allows sets of feature points to be related such that the aircraft position and orientation can be correlated to previous GPS data so that GPS-like navigation can be maintained in denied environments. The Volpe report acted as an impetus for many companies and institutions to investigate mitigation strategies for the vulnerabilities associated with the current GPS navigation aid protocol, nearly all follow- ing the suggested GPS backup methods that revert to the archaic/legacy methods. Unfortunately, these navigational modalities are limited by the range of their land-based transmitters, which are expensive and may not be feasible for remote or hazardous environments. Based on these restrictions, researchers have investigated local methods of estimating position when GPS is denied. Given the advancements in computer vision and control theory, monocular camera systems have received growing interest as a local alternative/collaborative sensor to GPS systems. One issue that has inhibited the use of a vision system as a navigational aid is the di¢ culty in reconstructing inertial measurements from the projected image. Current approaches to estimating the aircraft state through a camera system utilize the motion of feature points in an image. Current approaches to recover the inertial state of the aircraft via a camera system include linear or nonlinear estimation methods. In contrast to these estimation methods, a geometric approach is proposed in this paper that uses a series of homography relationships. Speci…cally, a new method is proposed to create a series of daisy-chained images in which the feature points can be related so that the inertial coordinates of an aircraft can be determined between each successive image. Through these relationships, GPS data can be linked with the image data to provide inertial measurements in navigational regions where GPS is denied. Recently, a similar method using homography relationships between images to estimate the pose of an aircraft were presented by Caballero, et al. 2 Their method is