# A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions
## 5 USV Applications for Preventive Maintenance and Disaster Response
### Search and Rescue
#### 5.3.1 USVs for SAR  
Preliminary work on SAR remounts to the second world war [24; 28]. However, documented research often mentions USVs for SAR starting in the late 1990s. In 1995, the University of Rostock developed in 1995 Rescue Dolphin, a USV for SAR of people in distress [24; 186]. The system automatically triggers an alarm in case of people overboard, activating the USV which rapidly moves toward the person adrift, securing the victim until the rescue by ship. According to [PERSON] [24], in the last decade, a Canadian company called (ISE) developed two vessels for SAR: the Seal USV, for demonstration purposes to Canadian Department of National Defense (DND); and the SARPAL, which can be deployed from the air. [PERSON] [28] mentions the Sterling USV, which can be used for SAR as well, along with several CRASAR initiatives involving USVs for DM. SAR operations using USVs often involve the use of different vision sensors, some background subtraction strategy, along with some object detection & tracking technique [187]. However, the scope of this section is not to address video and image processing techniques--interested users are referred to [187] as a starting point. In the same way, the scope of this work is also not coverage path planning or GNC, where relevant work and surveys are abundant and presented as background work--[188] is a recent and specific survey on coverage path planning. Below we address such works involving SAR and USVs directly. [PERSON] et al. [189] devised a multi-purpose USV, under the support of Innovation Program of Shanghai Municipal Education Commission, capable of performing water sampling, hydrographic surveys, and SAR missions. The USV is equipped with GPS and an infrared camera with a range of 100 m at night. The USV can carry more than 100 Kg of payload, to carry a person or lifesaving appliances to a castaway. Regarding detection of survivors in the water, [PERSON] et al. [190] describe a USV equipped with an Arduino-based system for human detection. There are also preliminary experiments emulating the search of human bodies after disaster events, conducted by [191; 192; 193]. [PERSON] et al. [193] devised a robust method for the detection of submerged bodies using ultrasound, which is difficult in turbid scenarios. The task is challenging, since underwater ultrasound image may not straightforwardly be converted into geometric shapes, mainly due to heavy noise on its characteristics. The authors make use of a Convolutional Neural Network and the Caffe framework to identify submerged bodies with good results in tests performed in a Lab pool. [PERSON] et al. [194] developed a satellite-guided SAR system, to be used in special ships and offshore platforms in case a person falls overboard. It consists of three main components: (1) A vast with an Automatic Identification System (AIS), worn by every crew member of a ship or offshore platform; (2) An autonomous twin-hull catamaran USV, referred to as the \"rescue vessel\" (described in detail in [195; 196]); A satellite-aided control station. When a person falls overboard, the AIS test activates upon contact with the water, and the SAR process starts. The vast uses a differential GPS to determine the person's position and broadcasts it to the control station as an AIS message. Upon receiving this message, the control station deploys the rescue vessel, which autonomously navigates to a minimum safe distance from the person. A human operator in the control station then assumes manual control, approaching a salvage position based on video information from the USV. After the person is rescued, the rescue vessel and control station ship navigate toward each other, at which point the USV is picked up by the control station ship, completing the rescue scenario. The authors tested USV for maneuvering, swell and free fall tests in the swell basin of the Technical University of Berlin, proving its feasibility at sea, with rough waves. A successful test of the full SAR system was performed in the port of Rostock, Germany.