51. Attitude and position estimation for an UAV swarm using consensus Kalman filtering
- Author
-
Gaetano Tartaglione, Massimiliano Mattei, Egidio D'Amato, Immacolata Notaro, D'Amato, E., Notaro, I., Mattei, M., Tartaglione, G., IEEE, and Mattei, Massimiliano
- Subjects
Attitude and Position Estimation ,Estimation ,Engineering ,Inertial frame of reference ,Basis (linear algebra) ,Consensun Estimation ,business.industry ,Aerospace Engineering ,Swarm behaviour ,Control engineering ,Unmanned Aerial Vehicle ,Kinematics ,Kalman filter ,Kalman Filtering ,Swarm ,Unmanned Aerial Vehicles ,Civil and Structural Engineering ,Instrumentation ,Position (vector) ,Control theory ,Instrumentation (computer programming) ,business - Abstract
This paper presents the application of a distributed attitude and position estimation algorithm to a swarm of cooperating UAVs with heterogeneous sensors on board. The algorithm, based on a Consensus Extended Kalman Filtering (CEKF) to account for nonlinearities, is implemented assuming kinematic relationships. Numerical simulations are presented on different flight scenarios to evaluate the benefits of dealing with prior and novel information in a separate way on the basis of recent theoretical results on CEKF. Inertial and vision sensors are supposed to be mounted on board of the aircraft. Realistic flight scenarios are analyzed in the light of possible time communication delays among the agents. © 2015 IEEE.
- Published
- 2015
- Full Text
- View/download PDF