# AUV Adaptive Sampling Methods: A Review
## 6 Conclusions  
The dynamic nature of the global ocean environment, non-holonomic characteristics of current AUVs and limited underwater communications present considerable challenges and restrictions for AUV operations. However, with recent advances in adaptive systems, underwater operations are slowly becoming more autonomous.  
A review of recent advances in adaptive sampling is presented in this paper. The methodologies and approaches are subdivided based on different targets, mission objectives and the number of sampling agents. Development of in-field sensor technology and in-situ sample analysis has allowed the detection of a variety of targets and to perform tasks with numerous mission objectives in the global ocean. Adaptive sampling methodologies have enabled enhanced autonomy in AUV operations. The advances in acoustic communications have allowed more coordinated and cooperative control among multiple vehicles.  
Researchers previously used multiple vehicles primarily to obtain simultaneous data at more than one point in an area of interest. Most multiple vehicle work to date has focused on a limited number of vehicles communicating with each other between a virtual body (leader) and follower agents. Their work has mainly focused on the multi-vehicle operation and trajectory design as opposed to the sampling behaviours. There is tremendous promise in operating multiple vehicles, especially once it becomes possible to operate swarms of vehicles obtaining many simultaneous data points. Limitations to date are primarily the limitations in underwater communication.  
Most adaptive sampling to date has been based on gradient methods. Problems such as the tracking and delineation of patchy oil plumes and the intermittent release of thermal vents need to be addressed and surveyed by using a new class of methods. The most promising methods for these problems, in some cases proposed and used for chemical plumes that are not continuous, have focussed on bio-mimetic approaches that have modelled bacterium, insect or marine crustacean behaviour. This is expected to be the direction of future adaptive sampling work in this area.  
To suit different mission characteristics, different types of search algorithm are valuable. AUV manufacturers producing vehicles for scientific missions are encouraged to provide adaptive mission capability on their vehicles, which might eventually include different search algorithms to tackle different problems of interest to the research community.  
The contribution from each author was as follows: conceptualization, J.H. and S.F.; methodology, J.H., S.F. and N.B.; formal analysis, J.H.; investigation, J.H.; resources, S.F. and N.B.; data curation, J.H.; writing--original draft preparation, J.H.; writing--review and editing, J.H., S.F. and N.B.; supervision, N.B. and S.F.; project administration, N.B.; funding acquisition, N.B. and S.F. (The initials represent the authors' initials).  
This research was supported by the Australian Research Council's Special Research Initiative under the Antarctic Gateway Partnership (Project ID SR140300001). Funding was also received from Fisheries and Oceans Canada through the Multi-partner Oil Spill Research Initiative (MPRI) 1.03: Oil Spill Reconnaissance and Delineation through Robotic Autonomous Underwater Vehicle Technology in Open and Iced Waters. The first author also acknowledges the Australian Government Research Training Program Scholarship in support of this higher degree research.  
The authors declare no conflict of interest.