Distributed Information Filters for MAV Cooperative Localization

نویسندگان

  • Andrea Cristofaro
  • Alessandro Renzaglia
  • Agostino Martinelli
چکیده

This paper introduces a new approach to the problem of simultaneously localizing a team of micro aerial vehicles (MAV) equipped with inertial sensors able to monitor their motion and with exteroceptive sensors. The method estimates a delayed state containing the trajectories of all the MAVs. The estimation is based on an Extended Information Filter whose implementation is distributed over the team members. The paper introduces two contributions. The former is a trick which allows exploiting the information contained in the inertial sensor data in a distributed manner. The latter is the use of a projection filter which allows exploiting the information contained in the geometrical constraints which arise as soon as the MAV orientations are characterized by unitary quaternions. The performance of the proposed strategy is evaluated with synthetic data. In particular, the benefit of the previous two contributions is pointed out.

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تاریخ انتشار 2010