## 3 Collaborative AUVs
### Collaborative Navigation
[11] developed an algorithm for AUVs navigating on a close formation, where light markers and artificial vision are used to allow the estimation of the pose of a target vehicle at short ranges with high accuracy and execution speed. In the experiments presented, the filtered pose estimates were updated at approximately 16 Hz, with a standard deviation lower than 0.2 m in the distance uncertainty between vehicles, at distances between 6 m and 12 m. As expected, the results showed that the system performs adequately for vehicle separations smaller than 10 m, while the tracking becomes intermittent for longer distances due to the challenging visibility conditions underwater. Other alternatives for cooperative navigation of AUVs is the use of systems that allow the vehicles within a team to help each other with their localization. [PERSON] et al. [132] proposed a TBN system for cooperative AUVs. The approach consists on an altimeter and acoustic modem equipped on each vehicle and a bathymetric terrain map. The localization is performed via decentralized particle filtering. The vehicles in the team are assumed to have their system time synchronized. A simple scheduling is adopted so that each vehicle in the team broadcasts its local state information sequentially using acoustic communication. This information includes the vehicle current position, the filter estimated covariance matrix, and the latest water depth measurement. When the acoustic signal is received by another vehicle the time-of-arrival can be calculated to determine the inter-vehicle distance. Results showed that localization performance improves as the number of the vehicles in the team increase, at least up to four, and when they are in range for a proper acoustic communication. The average positioning error was in the range of a few meters in those conditions. [PERSON] et al. [133] developed a cooperative path planning for range-only localization. Authors explored the use of a single-beacon vehicle for range-only localization to support other AUVs. Specifically, they focused on cooperative path-planning algorithms for the beacon vehicle using dynamic programming formulations. These formulations take into account and minimize the positioning errors being accumulated by the supported AUV. Implementation of the cooperative path-planning algorithms was in a simulated environment. The simulations were conducted with different types of ranging aids, each transmitted from a single beacon. The ranging aids used were: single fixed beacon, circularly moving beacon, and cooperative beacon. Experimental results were also obtained by a field trial was conducted near Serangoon Island, Singapore. Average error was reduced up to 19.1 m over a traveled distance of 1.5 km. [PERSON] et al. [134] made a similar approach. The problem addressed by the authors consisted of designing a relative localization solution for a networked group of vehicles measuring mutual ranges. The aim of the project was to exploit inter-vehicle communications to enhance the range-based relative position estimation. Vehicles are considered capable to know their own position, orientation, and velocity regarding a common frame. Such vehicles share their own information through their communication channel and they can obtain measurements of their relative Euclidean distance with respect to several other agents. The connection topology of the agents was represented through a relative position measurement graph and a simulation, relative to a group of 4 agents, was performed with different connection topologies. During the simulation, \(z\) error remained in the range of \(\pm\) 1 m after a time-lapse of 3000 s.