# A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions
## 8 Conclusions  
In this paper, we performed a review of state of the art in USVs for DM, focusing on both natural or man-made disasters. Most USV reviews focus on GNC, while the research involving USVs for DM is spread across different DM oriented publications, with focus on more than one unmanned vehicle and varying degrees of depth. This review is the first focused specifically on USVs for DM. As the present research features a broad research problem, its inherent challenge is the capacity to encompass all works on the field. We did our best to cover the field, but we may not have coveredall of it. We might have missed works as the project evolved and tasks were subdivided. Another challenge while studying USVs is the naming convention, which is not uniform--e.g., unmanned marine/surface crafts, vessels, vehicles, or autonomous or unmanned boats. Such a lack of naming conventions for USVs leads to a series of research problems, including exceeding character limits in search fields and difficulty while narrowing down relevant works. Furthermore, search engines can associate such acronyms with studies in physics, medicine, economics, history, and other unrelated fields. One way to address this is to use exclusion keywords in the search--e.g., excluding the word \"blood\" from the search. The term marine vehicle is also ambiguous, which may lead to UUVs or USVs. Similar problems occur with disaster keywords such as \"flood\", which is associated with network security. The use of exclusion words here also applies--e.g., excluding DDoS, hacking. Still, the primary research goal was to put USVs for DM in the spotlight--away from the generic UMV nomenclature. In this sense, we believe to have succeeded. This paper presents a list of current DM applications for USVs. While there are plenty of promising works on the field globally, most of them are still experimental and not fully developed. Among the uses of USVs in the DM process, we highlight some of the mature applications available--e.g., SAR; extreme weather forecast; seismic event forecast; structural inspection; and disaster impact assessments on the environment. Other recurrent motivations to use USVs are to move through dangerous scenarios where manned surface vehicles cannot go such as hurricanes or extreme weather regions at sea, to find routes through debris, or to perform inspection nearby dams or bridges. Also, in the event of an environmental disaster, such as large oil spills, USVs can quickly move toward the accident zone and perform environmental damage assessments such as measuring water contamination and water-life impact assessments. One of the surprising discoveries involves floods. Even though they are a recurrent motivator for USV research, the subject is not directly addressed. Often, the USV research addresses floods only in the recovery phase. In general, most researchers focus on technology and not on disaster-oriented mission results, even though disaster scenarios recurrently motivate them. Consequently, few papers test USVs in disaster sites or similar conditions. Therefore, it means that most papers do not address the effectiveness or efficiency of the USV in such extreme conditions. We speculate that as the research focus is often technology-oriented--i.e., typical control, GNC, multi-robot cooperation, and other fundamental research problems--tests in disaster scenarios are left as secondary future work. Another possible explanation is that research teams are usually not multidisciplinary enough to address the multifaceted research challenges involving DM. Even if a research team plans to do that, there are many problems to such a challenging endeavor. The main one is the cost of reproducing such extreme conditions in actual field trials. Today there are numerous competitions involving heterogeneous robotic systems which include USVs and few testing sites which emulate disaster scenarios. However, the cost of transporting the team and the robots to such sites is often unfeasible for many research institutions.