# A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions
## 1 Introduction  
_Natural disasters_ have severe consequences for the environment, human lives, and man-made constructions. Moreover, cities and often countries face severe social and economic distress as a result of a disaster. Extreme natural events such as the earthquakes/tsunamis that occurred in Tohoku (Japan, 2011), in the Indian Ocean (2004) and the hurricane in New Orleans flood (United States, 2005) are some examples. These natural phenomena result in problems which can be felt even years after the disaster. They usually cause damage to utility infrastructure, affecting electricity, natural gas, water, sewage, communications, roads, bridges, and transportation services. Furthermore, damages at facilities such as natural gas pipes, dams, or nuclear power plants can cause even more massive disasters. On the other hand, _man-made disasters_ can produce consequences as severe as the natural ones. Oil spills, mine waste floods, heavy metal, and radioactive contamination, wildfire caused by humans directly are examples of disasters with non-natural starts. Examples are the Deepwater Horizon oil spill (United States, 2010), Chernobyl disaster (Ukraine, 1986), Bento Rodrigues Dam disaster (Brazil, 2015) and California wildfires (United States, 2018). Despite the origin of the disaster (i.e., natural or man-made), it can affect the quality of potable water, crops, and cattle, affecting food provisioning for entire regions. It can also cause catastrophic damage to nature, profoundly affecting local communities. All of those can lead to substantial economic losses, the spread of diseases, or even mental issues caused by the disaster trauma. The lack of such basic needs may also result in public social calamity. Over the years, there has been a growing awareness [1] about disasters, either natural or man-made, and the need for measures to reduce their impact. The problem is not only the disaster itself but also how the affected region is prepared to face it [2]. Disaster Management (DM) can be divided into four different stages [3]: mitigation, preparedness, response, and recovery. The stages preceding the disaster occurrence, i.e., mitigation and preparedness, define how well the community can respond and recover from it. The DM process currently demands better tools (more reliable, easy to use, more efficient, cheaper, etc.) for the phases preceding and after disasters. Robotics is becoming a recurrent source of tools in disaster applications. For example, regarding data acquisition applications, unmanned vehicles can play an essential role for disaster research [4] by replacing response teams in remote and hazardous environments [5], or performing long-term monitoring [6]. Unmanned vehicles have been deployed in the three main types of environments: aerial, ground, and aquatic. Most of the papers related to robotics and DM are related to ground, underwater, and unmanned aerial vehicles. Surprisingly, on this topic, the presence of Unmanned Surface Vehicles (USVs) [7] seems to have fallen behind those of other platforms [8; 9], such as Unmanned Aerial Vehicles [10] (UAVs) and Unmanned Underwater Vehicles [11; 12] (UUVs). As far as we known, this is the first survey of USVs for DM applications. On the water surface, USVs stand out from other unmanned aquatic platforms for data collection due to: access to Global Positioning System (GPS) and other localization strategies [13; 14]; superior communication capabilities when compared to other marine vehicles [15; 16]; payload capacity; and capacity to use energy harvesting (solar, waves, wind) for long-term missions. Also, USVs can be seen as moving sensors, which can quickly perform several measurements in different locations, or even be deployed for emergency relief tasks in remote areas. Hence, the _main contribution_ of this paper is a systematic review of USVs for DM and their role in disaster scenarios.