Abstract
This paper discusses the exploitation of a cooperative navigation strategy for improved in-flight estimation of inertial sensors biases on board unmanned aerial vehicles. The proposed multi-vehicle technique is conceived for a “chief” Unmanned Aerial Vehicle (UAV) and relies on one or more deputy aircrafts equipped with Global Navigation Satellite System (GNSS) antennas for differential positioning which also act as features for visual tracking. Combining carrier-phase differential GNSS and visual estimates, it is possible to retrieve accurate inertial-independent attitude information, thus potentially enabling improved bias estimation. Camera and carrier-phase differential GNSS measurements are integrated within a 15 states extended Kalman filter. Exploiting an ad hoc developed numerical environment, the paper analyzes the performance of the cooperative approach for inertial biases estimation as a function of number of deputies, formation geometry and distances, and absolute and relative dynamics. It is shown that exploiting two deputies it is possible to improve biases estimation, while a single deputy can be effective if changes of relative geometry and dynamics are also considered. Experimental proofs of concept based on two multi-rotors flying in formation are presented and discussed. The proposed framework is applicable beyond the domain of small UAVs.
Highlights
Nowadays, Unmanned Aerial Vehicles (UAVs) represent a popular solution for executing tasks in several markets and applications [1], such as delivery of goods [2], surveillance and monitoring [3], inspection and mapping [4], precision agriculture [5], and cinematography [6].The usage of flying platforms allows reducing time and cost of the mission, while guaranteeing high flexibility
UAV navigation is usually tackled by fusing inertial and Global Navigation Satellite System (GNSS) measurements, which for their complementary properties are usually combined in Kalman filters (KF)
Results obtained with cooperation and without cooperation have been reported in black and blue, respectively
Summary
The usage of flying platforms allows reducing time and cost of the mission, while guaranteeing high flexibility. This improves mission performance and/or enables missions which were not feasible at all. Inertial measurements consist of three axes gyroscopes’ and accelerometers’ observables, retrieved with an inertial measurement unit (IMU). These measurements are affected by different error sources including a time-varying in-run bias for each channel, which if not correctly estimated, can spoil the performance in positioning, velocity, and attitude estimate. Residual uncompensated inertial biases may play a key role in the positioning error growth rate in absence of reliable GNSS coverage
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