Dynamic positioning of beacon vehicles for cooperative underwater navigation

Autonomous Underwater Vehicles (AUVs) are used for an ever increasing range of applications due to the maturing of the technology. Due to the absence of the GPS signal underwater, the correct estimation of its position is a challenge for submerged vehicles. One promising strategy to mitigate this problem is to use a group of AUVs where one or more assume the role of a beacon vehicle which has a very accurate position estimate due to an expensive navigation suite or frequent surfacings. These beacon vehicles broadcast their position and the remaining survey vehicles can use this position information and intra-vehicle ranges to update their position estimate. The effectiveness of this approach strongly depends on the geometry between the beacon vehicles and the survey vehicles. The trajectories of the beacon vehicles should thus be planned with the goal to minimize the position uncertainty of the survey vehicles. We propose a distributed algorithm which dynamically computes the locally optimal position for a beacon vehicle using only information obtained from broadcast communication of the survey vehicles. It does not need prior information about the survey vehicles' trajectory and can be used for any group size of beacon and survey vehicles.United States. Office of Naval Research (Grant N00014-97-1-0202)United States. Office of Naval Research (Grant N00014-05-1-0255)United States. Office of Naval Research (Grant N00014-02-C- 0210)United States. Office of Naval Research (Grant N00014-07-1-1102

Minimizing Trilateration Errors in the Presence of Uncertain Landmark Positions

Abstract—Trilateration is a technique for position estimation from range measurements which is often used in robot navigation. Most applications assume that there is no error associated with the landmarks used for trilateration. In cooperative navigation, in which groups of robots use each other as mobile beacons for position estimation, it is imperative to take the uncertainty in the beacon position into account. In this paper, we model the position uncertainty of a landmark using a multivariate Gaussian distribution and show how the uncertain landmark position translates to an uncertainty in the trilaterated position. We provide insights into how the optimal trilateration point for a fixed geometry of landmarks depends on the distribution of the position error. This provides a metric for guiding the motion of a robot to maintain favorable trilateration geometries when navigating relative to other robots whose positions are imprecisely known

Ad-Hoc Personenlokalisierung in Drahtlosen Sensornetzwerken

In der Arbeit wird ein neues Konzept zur ad-hoc Personenlokalisierung entwickelt und untersucht. Ansätze aus dem Bereich der Lokalisierung in selbstkonfigurierenden, drahtlosen Sensornetzwerken sowie aus dem Bereich der inertialsensorbasierten Personennavigation werden verwendet und zu einem hybriden Lokalisierungsansatz kombiniert. Eine umfangreiche, experimentelle Studie wird durchgeführt. Im Ergebnis wird ein Ansatz aufgezeigt, wie sich Personen in ad-hoc Szenarien lokalisieren lassen