Relative positioning for underwater navigation of multi-vehicle systems
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Özet (EN)
Precise and accurate navigation is a significant problem for Autonomous Underwater Vehicle (AUV) applications. Due to limited electromagnetic penetration, GPS sensors are not an option for determining the position of an AUV. The most common method is called dead reckoning, which uses inertial measurement units (IMUs) with accelerometers and gyroscopes. Bias errors, misalignment and noisy measurements are common problems with IMUs. These errors make position information to be unreliable over long periods of time. Position errors grow rapidly due to velocity and angular random walk. The problem is further complicated when more than one vehicle is involved in a series of underwater tasks. Although conventional acoustic systems such as long baseline and ultra-short baseline have been developed to overcome the navigation problem, they are logistically complex and only cover a pre-deployed area. The process of deploying transponders and initialising them with precisely known locations makes the systems expensive and inappropriate for low cost AUVs. In order to eliminate growing errors of dead reckoning method, a system architecture with a navigation algorithm for N vehicles is proposed. This architecture makes use of a simple acoustic measurement system and a filtering algorithm. The simplicity of this acoustic measurements reduces the logistic complexities of conventional systems greatly. A leader-follower formation control is implemented, where there is a leader AUV and N-1 follower AUVs. The system obtains relative positions between the leader and its followers, rather than absolute positions, to keep the formation intact. The follower AUVs position themselves according to the leader. This allows coordinated movements such as synchronised turns and manoeuvres without breaking the formation.
Yazar
Göksel Berker Gönül
Kurum
Bu Yayına Nasıl Atıf Yapılır
Göksel Berker Gönül (Master Thesis). Relative positioning for underwater navigation of multi-vehicle systems, 2023, Boğaziçi University.
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