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Abstract
Velocity updates have been proven to be important for constraining motion-sensor-based dead-reckoning (DR) solutions in indoor unmanned aerial vehicle (UAV) applications. The forward velocity from a mass flow sensor and the lateral and vertical non-holonomic constraints (NHC) can be utilized for three-dimensional (3D) velocity updates. However, it is observed that (a) the quadrotor UAV may have a vertical velocity trend when it is controlled to move horizontally; (b) the quadrotor may have a pitch angle when moving horizontally; and (c) the mass flow sensor may suffer from sensor errors, especially the scale factor error. Such phenomenons degrade the performance of velocity updates. Thus, this paper presents a multi-sensor integrated localization system that has more effective sensor interactions. Specifically, (a) the barometer data are utilized to detect height changes and thus determine the weight of vertical velocity update; (b) the pitch angle from the inertial measurement unit (IMU) and magnetometer data fusion is used to set the weight of forward velocity update; and (c) an extra mass flow sensor calibration module is introduced. Indoor flight tests have indicated the effectiveness of the proposed sensor interaction strategies in enhancing indoor quadrotor DR solutions, which can also be used for detecting outliers in external localization technologies such as ultrasonics.
Highlights
Unmanned aerial vehicles (UAV) have shown great potential in civilian applications such as indoor/outdoor mapping [1], target tracking [2], victim searching [3], and industrial inspection [4]
The integration of data from the inertial measurement units (IMU), magnetometers, barometer, and mass flow sensor can provide a short-term accurate DR solution, the solution will drift over time when an absolute update is not available
The quadrotor was equipped with an InvenSense MPU6000 mechanical systems (MEMS)-based IMU [54], a Honeywell HMC 5983 magnetometer triad [55], a TE MS5611 barometer
Summary
Unmanned aerial vehicles (UAV) have shown great potential in civilian applications such as indoor/outdoor mapping [1], target tracking [2], victim searching [3], and industrial inspection [4] For these applications, a key is the real-time estimation of UAV navigation states (i.e., position, velocity, and attitude). Have been successfully commercialized to provide accurate (i.e., decimeter and centimeter level location accuracy for dynamic and static applications, respectively) location solutions in outdoor areas [5], reliable indoor UAV localization is a challenge due to the degradation of GNSS signals To alleviate this issue, researchers have presented various systems and approaches. The used sensors and algorithms are shown as well as their test areas and location accuracies
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