# AUV Adaptive Sampling Methods: A Review
## 5 Multiple Platforms Networking
### Multiple Agents Networking
improved the federated decentralised filter by modifying the formulation; hence, decomposing the full-order filtering. It was referred to as the federated distributed filter. Unlike a federated decentralised filter, it calculated the local field estimates instead of the entire field. Both reduced computational complexity and a drastic reduction of communication could be achieved. When multi-vehicles are involved to localise the source of the field of interest, they can either retain a fixed group formation or have a dynamic, more flexible formation [104]. One example of a fixed formation is a combination of a leader-follower approach presented by [PERSON] et al. [105] utilising ASVs and AUVs. It is a gradient-based chemotaxis of three vehicles. The approximated gradient of the scalar field is collected by the vehicles. When the intensity exceeds certain thresholds, the group follows the gradient until the source is found. [PERSON] et al. [106] introduced a formation-control-based anemotaxis approach (organisms responding to wind) on two-dimensional space. In their method, the source was determined by odour measurements obtained by all vehicles in a group. They conducted a wind-tunnel experiment using a three-agent inverted V, three-agent linear and five-node square formation with a flexible distance between nodes. The selected formation was maintained using the Laplacian feedback formation control [107]. Inspired by the autonomous ocean sampling network (AOSN) utilising coordinated sampling efforts, several other multi-agent control systems have been demonstrated. The Glider Coordinated Control System (GCCS) enabled the automated navigation of a glider fleet to maintain the sampling trajectory [108]. The sampling trajectory was adaptively defined based on objective analysis (OA); hence, the fleet could perform an optimal sampling. However, GCCS did not take into consideration the flow field in their sampling plan. Their approach might not be applicable for a highly dynamic flow. [PERSON] et al. [109] developed an automated software for controlling a fleet of gliders. Their vehicle-oriented system could assimilate data obtained from the gliders and satellites so that new \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Pure Centralised Filter** & **Pure Decentralised Filter** & **Federated Decentralised Filter** \\ \hline Process: Sensor measurements from multiple vehicles are transmitted to the central filter. Then, the field estimates are calculated. & Process: Carrying and utilising its own filter, each sensor platform takes measurements and computes partial estimates. & Process: Each vehicle takes measurements. Local estimates are computed and transmitted to the global fusion filter then complete estimates are transmitted back to all vehicles. & Process: Each vehicle takes measurements. Local estimates are computed and transmitted to the global fusion filter then complete estimates are transmitted back to all vehicles. & Process: Each vehicle takes measurements. Local estimates are computed and transmitted to the global fusion filter then complete estimates are transmitted back to all vehicles. & Measurements: Local estimates are computed and transmitted to the global fusion filter then complete estimates are being carried the whole time. Not efficient communication. \\ \hline \hline \end{tabular}
\end{table} 
Table 16: Comparison of three schemes of Kalman filters (KF) in the adaptive sampling algorithm. missions for the fleet could be generated adaptively. Their strategy was demonstrated in multi-vehicle operation in the New York Bight and on the West Coast Florida Shelf. Fleet logistical interface and control software (FLICS) was developed for micro-unmanned underwater vehicles (UUVs) operation (from preparation to recovery) such as formation control, mapping, plume source seeking and adaptive cooperation [110]. The 5 kg UUVs demonstrated adaptive cooperative missions in Newport River, North Carolina, USA.