Title :
Cooperative navigation of MAVs In GPS denied areas
Author :
Sharma, Rajnikant ; Taylor, Clark
Author_Institution :
Deaprtment of Electr. & Comput. Eng., BYU, Provo, UT
Abstract :
Cooperative missions for Miniature Air Vehicles (MAVs) require accurate position, velocity, and attitude estimates for all MAVs within the group for its successful completion. This paper details a cooperative methodology for MAV navigation in times of Global Positioning System (GPS) outages or in GPS denied areas. In this method, each MAV estimates position, attitude, and velocity of all MAVs in its sensor range, including itself. Each MAV collects the IMU measurements from each of the neighboring MAVs and fuses these measurements with relative range and bearing measurements taken of every MAV in its sensor range. This collected data is then used to estimate navigation states using an Extended Kalman Filter (EKF). Simulation results presented in this paper demonstrate that this Cooperative Navigation System (CNS) can effectively constrain pose estimation drift in the absence of GPS. We also performed the nonlinear observability analysis to support the improved performance of CNS.
Keywords :
Global Positioning System; aerospace robotics; aircraft; microrobots; path planning; pose estimation; remotely operated vehicles; sensor fusion; cooperative missions; cooperative navigation system; extended Kalman filter; global positioning system; miniature air vehicles; nonlinear observability analysis; pose estimation drift; sensor range; Acceleration; Fuses; Global Positioning System; Intelligent systems; Intelligent vehicles; Navigation; Observability; Sensor fusion; State estimation; Unmanned aerial vehicles;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 2008. MFI 2008. IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-2143-5
Electronic_ISBN :
978-1-4244-2144-2
DOI :
10.1109/MFI.2008.4648041