Comparative analysis of feature-based methods and direct methods for unmanned system’s vision navigation

Abstract

Vision navigation is an alternative to Global Position System (GPS) in environments where access to GPS is denied, and cameras’ pose estimation is the key technology. At present, the pose estimation methods can be divided into two main techniques: feature-based methods and direct methods. In this paper, we theoretically analyzed the basic principles of feature-based methods and direct methods. The Jacobian matrix of cost function with respect to the pose represented by Lie algebra is derived in detail. Then the nonlinear optimization method is utilized to obtain the optimal camera pose. Finally, the accuracy, real-time and robustness of the two methods are compared and analyzed through systematic and comprehensive experiments.