摘要

Range-only measurements are extensively used in many Autonomous Underwater Vehicle (AUV) applications. These measurements do not depend on water quality and can be taken from long distances. This paper proposes two methods based on the Sum of Gaussian (SoG) filter, to solve the range-only localization problem for homing. The use of the SoG allows us to combine the benefits of both a Particle Filter (PF) and an Extended Kalman Filter (EKF) approach in a single filter. An Active Localization (AL) method is applied to the SoG to autonomously choose the best waypoints for autonomous convergence. Both the SoG filter and the AL are tested in a real scenario with an Intervention Autonomous Underwater Vehicle (I-AUV) and compared with a vision-based method to confirm localization.

  • 出版日期2016