Autonomy through SLAM for an Underwater Robot

摘要

Abstract An autonomous underwater vehicle (AUV) is achieved that integrates state of the art simultaneous localization and mapping (SLAM) into the decision processes. This autonomy is used to carry out undersea target reacquisition missions that would otherwise be impossible with a low-cost platform. The AUV requires only simple sensors and operates without navigation equipment such as Doppler Velocity Log, inertial navigation or acoustic beacons. Demonstrations of the capability show that the vehicle can carry out the task in an ocean environment. The system includes a forward looking sonar and a set of simple vehicle sensors. The functionality includes feature tracking using a graphical square root smoothing SLAM algorithm, global localization using multiple EKF estimators, and knowledge adaptive mission execution. The global localization incorporates a unique robust matching criteria which utilizes both positive and negative information. Separate match hypotheses are maintained by each EKF estimator allowing all matching decisions to be reversible. 1