Vision-aided localization and navigation based on trifocal tensor geometry

In this paper, a new method for vision-aided navigation based on trifocal tensor geometry is presented. The main goal of the proposed method is to estimate the position of vehicles in global positioning system-denied environments, using a standard inertial navigation system and only a single camera. The geometric trifocal tensor relationship between three images is used as measurement information from the camera, and the primary contribution of this work is the derivation of a measurement model that is able to express the geometric constraints of the trifocal tensor in the global frame. This measurement model does not require including the three-dimensional feature positions in the state vector. In other words, the proposed method does not entail reconstructing the environment. Rather, the method only considers the vehicle state. The vision-aided inertial navigation algorithm that we propose has computational complexity only with regard to the number of features at the current time, and the algorithm is capable of estimating the pose in real environments. Experiments were conducted to show the effectiveness of the proposed method in simulations and real environments.