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The operation of mobile robots in unknown environments typically requires building maps during exploration. As the exploration time and environment size increase, the amount of data collected and the number of variables required to represent these maps both grow, which is problematic since all real robots have finite resources. The solution proposed in this paper is to only retain the variables and...
This paper investigates the problem of cooperative navigation of autonomous marine vehicles using range-only acoustic measurements. We consider the use of a single maneuvering autonomous surface vehicle (ASV) to aid the navigation of one or more submerged autonomous underwater vehicles (AUVs), using acoustic range measurements combined with position measurements for the ASV when data packets are transmitted...
In this paper we address the problem of drift-free navigation for underwater vehicles performing harbor surveillance and ship hull inspection. Maintaining accurate localization for the duration of a mission is important for a variety of tasks, such as planning the vehicle trajectory and ensuring coverage of the area to be inspected. Our approach only uses onboard sensors in a simultaneous localization...
Tracking sonar features in real time on an underwater robot is a challenging task. One reason is the low observability of the sonar in some directions. For example, using a blazed array sonar one observes range and the angle to the array axis with fair precision. The angle around the axis is poorly constrained. This situation is problematic for tracking features in world frame Cartesian coordinates...
A robot exploring an environment can estimate its own motion and the relative positions of features in the environment. Simultaneous localization and mapping (SLAM) algorithms attempt to fuse these estimates to produce a map and a robot trajectory. The constraints are generally non-linear, thus SLAM can be viewed as a non-linear optimization problem. The optimization can be difficult, due to poor...
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