Abstract

DORVIGNY DORVIGNY, Darvis; HERNANDEZ SANTANA, Luis  and  GARCIA GARCIA, Delvis. Integrated navigation algorithm for autonomous vehicles with low cost technology. Rev cuba cienc informat [online]. 2018, vol.12, n.3, pp. 121-139. ISSN 2227-1899.

Interest in the development of autonomous vehicles has grown in recent years, due to the possibilities they offer for the accomplishment of missions in places difficult to reach, in reconnaissance tasks, in the study of ecosystems, and in other important branches such as agriculture . In Cuba, the Group of Automatation, Robotics and Perception of the Universidad Central Marta Abreu de las Villas, together with other institutions, it is intended to develop autopilots for autonomous vehicles. This paper presents a navigation solution based on the Kalman Extended Filter. Low-cost inertial sensor measurements are indirectly fused with GPS measurements to estimate the position and speed of an autonomous vehicle. The fundamental equations for the implementation of a complementary filter to estimate the orientation of the vehicle, very important for navigation, are addressed as added value. The simulation was performed with real data of an underwater vehicle, using Matlab. The results show that the estimation of the navigation parameters is feasible for this type of application.

Keywords : Extended Kalman Filter; INS/GPS integration; navigation parameters; attitude and heading estimation.

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