INTEGRATED SYSTEM SIMULTANEUS LOCALIZATION AND MAPPING

Abstract

In this paper, we consider the solution of the problem of simultaneous localization and the construction of a map for an unmanned aerial vehicle (a quadrocopter). The structure of the integrated navigation system is developed on the basis of the fusion of several sources of navigational information, which allows to compensate the shortcomings of each source, which includes the following blocks: an improved system of visual navigation based on the use of EKF-SLAM, satellite navigation system GPS, barometric altimeter, radio altimeter, Strapdown inertial navigation system, the converter of modes of navigation. To improve the quality of the visual navigation system, an improved EKF-SLAM algorithm is proposed with the adaptation of the surveillance zone and local data association based on the improved ants algorithm, thereby avoiding obstacles. Recognition of landmarks is based on the use of the algorithm SURF. The EKF-SLAM algorithm is integrated through Adaptive Observation Range. Algorithms for dynamically changing the size of the observation zone and determining the redundancy of the detected landmarks are proposed. The extended Kalman filtering procedure for the problem under consideration and the proposed improvements are given. It is shown that the problem of SLAM data association can be represented as an optimization problem. As an optimization algorithm, an ant algorithm is proposed.