Distributed Information Filters for MAV Cooperative Localization

Andrea Cristofaro 1 Alessandro Renzaglia 1 Agostino Martinelli 1
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : 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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Andrea Cristofaro, Alessandro Renzaglia, Agostino Martinelli. Distributed Information Filters for MAV Cooperative Localization. 10th International Symposium on Distributed Autonomous Robotics Systems (DARS), Nov 2010, Lausanne, Switzerland. ⟨inria-00537813⟩

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