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In an application involving Autonomous Underwater Vehicles (AUV) it is important to track the trajectory and spatially correlate the collected data. Relying on an Inertial Navigation System (INS) while factoring in the initial AUV position would not suffice given the major accumulated errors. Employing surface nodes is a logistically complicated option, especially for missions involving emerging events. This paper proposes a novel localization approach that offers both agility and accuracy. The idea is to exploit a communication mechanism across the air-water interface. In particular, we employ an airborne unit, e.g., a drone, that scans the area of interest and uses visual light communication (VLC) to reach the AUV. In essence, the airborne unit defines virtual anchors with known GPS coordinates. The AUV uses the light intensity of the received VLC transmissions to estimate the range relative to the anchor points and then determine its own global coordinates at various time instances. The proposed approach is validated through extensive simulation experiments. The simulation results demonstrate the viability of our approach and analyze the effect of the VLC parameters.
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Synergistic AUV Navigation through Deployed Surface Buoys
In this paper, we present a navigation method for an Autonomous Underwater Vehicle (AUV) in an underwater environment making use of a deployed set of static water surface platforms called buoys on the environment. Our method has the following steps: 1) Communication regions of buoys are computed from their communication capabilities; 2) A set of feasible paths through buoys between given initial and goal locations is calculated using the preimages of the buoys' communication regions; 3) An AUV navigation path that utilizes the least number of buoys for state estimation is chosen from the calculated feasible paths. Through extensive simulations, we validated our method which demonstrates its applicability.
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- PAR ID:
- 10282226
- Date Published:
- Journal Name:
- 2020 Fourth IEEE International Conference on Robotic Computing (IRC)
- Page Range / eLocation ID:
- 83 to 86
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IRC.2020.00020
