Cooperative Localization for GNSS-Denied Subterranean Navigation: A UAV–UGV Team Approach

Abstract

This paper presents a cooperative navigation architecture in a global navigation satellite system (GNSS)-denied subterranean environment using an unmanned ground vehicle (UGV) and unmanned aerial vehicle (UAV) team. The main focus of this design is to prolong the UAV mission time by reducing the UAV payload, sensing, and computational elements. To accomplish this, the UGV handles the mapping of the environment, its own state estimation, and the state estimation of the UAV using the UAV’s proprioceptive sensors, a three-dimensional lidar, and an ultra-wideband ranging radio that communicates with a similar radio on the UAV. The UAV is assumed to be instrumented with an inertial measurement unit, stereo camera, and laser altimeter, and the data from these instruments are shared with the UGV over a local network for use in UAV state estimation. This paper presents the architecture for localization of a UAV/UGV team and realizes the implementation using two different nonlinear state estimators. Details and a comparison between an extended Kalman filter and an incremental factor graph optimization implementation are provided. The performance of the presented algorithms is analyzed via experiments conducted in a motion-capture facility.