Sliding mode three-dimension SLAM with application to quadrotor helicopter

Unmanned Aerial Vehicles (UAV) systems have increased their applications, however, in different environments, it is not possible to obtain the location with devices such as the Global Positioning System (GPS). Also, in exploration applications, it is required to build maps with these systems. In this paper, the navigation of a quadcopter is carried out where an algorithm is proposed to solve the Simultaneous Localization And Mapping (SLAM) problem. Therefore, the Extended Kalman Filter (EKF) is one of the most used techniques to perform SLAM in different robots. However, one of the restrictions of the EKF asks that the uncertainties must be of the Gaussian type wirh zero-mean. For this reason, we propose the SM-SLAM algorithm to relax this restriction, in such a way, the algorithm is robust against bounded perturbations. The results obtained from the proposed algorithm are compared with the EKF-SLAM.

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