## 5 Conclusions and Future Works  
This paper presented a survey on the mission planning and management architectures for underwater cooperative robotics. Before exploring the mission planning and management details the architectures explored in the survey, a set of four features have been identified: mission plan specification, self-adaptation, virtualization, and mission plan dispatching and execution. Accordingly, we have defined a set of categories for each feature to facilitate the assessment of the explored features.  
This survey differs from others as it focuses mainly in the mission planning and management, but also in the set of features considered for the comparison among the different architectures.  
An assessment of the selected architectures based on the chosen features has been carried out. From the results, we cannot ignore that despite these architectures have been used successfully, there are still problems related to the mission management that have to be faced in future improvements and new designs. It can be foreseen that future works improving the current mission planning and management for cooperative robotics, in underwater environments or in any other unreliable and uncertain domain, or any new mission manager designed from the scratch should emphasize in the following aspects:  
* The use of a formal mission plan specification would allow, or at least facilitate, the reuse of the mission planning and management in other domains of application, requiring only minor changes.
* Self-adaptation should be considered at every level of the architecture, including the AUVs, the mission manager, and the whole architecture. A decentralized control for self-adaptive systems should be taken into account.
* Virtualization, or at least the abstraction of the agents' capabilities should be taken into account to allow for the reusability of the mission manage with legacy and new systems, requiring only to implement the corresponding adapter for each new agent as a virtual representation.
* Dispatching and execution of the mission plan should be defined carefully, and taking into account the limitations of the environment in which the agents will execute the mission plan, and also some other security and safety concerns that may prevent an agent to be able to receive subsequent tasks in a mission plan.
* Additionally, it could be of interest to explore the use of probabilistic planning for uncertain environments, as well as other techniques that do not rely only on the use of a subsumption approach.  
**Author Contributions:** Conceptualization, N.L.M. and P.C.; Funding acquisition, J.-F.M.-O.; Investigation, N.L.M.; Methodology, N.L.M.; Project administration, J.-F.M.-O.; Resources, N.L.M.; Supervision, J.-F.M.-O., P.C. and V.B.M.; Writing--original draft, N.L.M.; Writing--review & editing, N.L.M., P.C. and V.B.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** The research leading to the presented results has been partially undertaken within the SWAMRs European project (Smart and Networking Underwater Robots in Cooperation Meshes), under Grant Agreement n. 662107-SWARMs-ECSEL-2014-1, partially supported by the ECSEL JU and the Spanish Ministry of Economy and Competitiveness (Ref: PCIN-2014-022-C02-02).  
**Acknowledgments:** In this section you can acknowledge any support given which is not covered by the author contribution or funding sections. This may include administrative and technical support, or donations in kind (e.g., materials used for experiments).  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.