Abstract
Traditional methods used for navigating miniature unmanned aerial vehicles (MAVs) consist of fusion between Global Positioning System (GPS) and Inertial Measurement Unit (IMU) information. However, many of the flight scenarios envisioned for MAVs (in urban terrain, indoors, in hostile (jammed) environments, etc.) are not conducive to utilizing GPS. Navigation in GPS-denied areas can be performed using an IMU only. However, the size, weight, and power constraints of MAVs severely limits the quality of IMUs that can be placed on-board the MAVs, making IMU-only navigation extremely inaccurate. In this paper, we introduce a Kalman filter based system for fusing information from two additional sensors (an electro-optical camera and differential air pressure sensor) with the IMU to improve the navigation abilities of the MAV. We discuss some important implementation issues that must be addressed when fusing information from these sensors together. Results demonstrate an improvement of at least 10x in final position and attitude accuracy using the system proposed in this paper.
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© 2009 Springer-Verlag Berlin Heidelberg
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Taylor, C.N. (2009). Enabling Navigation of MAVs through Inertial, Vision, and Air Pressure Sensor Fusion. In: Hahn, H., Ko, H., Lee, S. (eds) Multisensor Fusion and Integration for Intelligent Systems. Lecture Notes in Electrical Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89859-7_11
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DOI: https://doi.org/10.1007/978-3-540-89859-7_11
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