Development of an Unmanned Surface Vehicle for the Emergency Response Mission of the ‘Sanchi’ Oil Tanker Collision and Explosion Accident
Development of an Unmanned Surface Vehicle for the Emergency Response Mission of the ‘Sanchi’ Oil...
Pu, Huayan;Liu, Yuan;Luo, Jun;Xie, Shaorong;Peng, Yan;Yang, Yi;Yang, Yang;Li, Xiaomao;Su, Zhou;Gao, Shouwei;Shao, Wenyun;Zhu, Chuang;Ke, Jun;Cui, Jianxiang;Qu, Dong
2020-04-14 00:00:00
applied sciences Article Development of an Unmanned Surface Vehicle for the Emergency Response Mission of the ‘Sanchi’ Oil Tanker Collision and Explosion Accident Huayan Pu, Yuan Liu , Jun Luo, Shaorong Xie, Yan Peng *, Yi Yang, Yang Yang, Xiaomao Li, Zhou Su, Shouwei Gao, Wenyun Shao, Chuang Zhu, Jun Ke, Jianxiang Cui and Dong Qu School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China; phygood_2001@shu.edu.cn (H.P.); liuyuanji@shu.edu.cn (Y.L.); luojun@shu.edu.cn (J.L.); srxie@shu.edu.cn (S.X.); yiyangshu@shu.edu.cn (Y.Y.); yangyang_shu@shu.edu.cn (Y.Y.); lixiaomaosia@163.com (X.L.); zhousuieee@126.com (Z.S.); swgao@shu.edu.cn (S.G.); shangdajiaoshi@shu.edu.cn (W.S.); zhuchuan@i.shu.edu.cn (C.Z.); sus_ke@126.com (J.K.); cjx8790@126.com (J.C.); qd0821@163.com (D.Q.) * Correspondence: pengyan@shu.edu.cn Received: 19 March 2020; Accepted: 10 April 2020; Published: 14 April 2020 Abstract: Unmanned surface vehicles (USVs) as unmanned intelligent devices can replace humans to perform missions more eciently and safely in dangerous areas. However, due to the complex navigation environment and special mission requirements, USVs face many challenges in emergency response missions for marine oil spill accidents. To solve these challenges in the emergency response mission of the ‘Sanchi’ oil tanker collision and explosion accident, we designed and deployed an USV to perform the missions of real-time scanning and water sampling in the shipwreck waters. Compared with the previous USVs, our USV owned the following characteristics: Firstly, the improved navigation control algorithms (path following and collision avoidance) can provide high navigation accuracy while ensuring navigation safety; Secondly, an improved launch and recovery system (LARS) enabled the USV to be quickly deployed and recovered in the mission area; Thirdly, a new sampling system was specially designed for the USV. Our USV completed the missions successfully, not only providing a lot of information for rescuers but also oering a scientific basis for follow-up work. Keywords: unmanned surface vehicle; marine oil spill; emergency response 1. Introduction On 6 January 2018, the Iranian oil tanker ‘Sanchi’ carrying 111,300 tons of condensate collided with the Hong Kong cargo ship ‘Changfeng Crystal’ in the East China sea, at approximately 160 nautical miles east of Shanghai. After the collision, the ‘Sanchi’ burned violently and exploded on 14 January. The ‘Sanchi’ sank 4 h after the explosion. Three people died and 29 people were missing in the accident, and oil leaked from the ‘Sanchi’ polluted 10 km of sea area. After the accident, the State Oceanic Administration of China, the Maritime Search and Rescue Center of China, and the Maritime Search and Rescue Center of Shanghai launched the emergency response mission for the accident. Figure 1 is the scene of the accident. In this accident, the ‘Sanchi’ oil tanker carried a total of 113,000 tons of condensate. Condensate is a highly toxic and volatile chemical substance, and there is a risk of deflagration at any time after it leaks. Therefore, it is too dangerous for humans to enter the core area of the accident to perform a mission. We urgently needed a mobile unmanned platform to replace humans in the core area of the accident to obtain the necessary information, such as the submarine topography, the state of the shipwreck, the location of oil spills, and the situation of water pollution. Appl. Sci. 2020, 10, 2704; doi:10.3390/app10082704 www.mdpi.com/journal/applsci Appl. Sci. 2020, 10, 2704 2 of 21 Appl. Sci. 2020, 10, x FOR PEER REVIEW 2 of 21 Figure 1. Accident scene. Figure 1. Accident scene. Unmanned In this accid surface ent, theve ‘Shicles anchi’(USVs) oil tank ar ee r c the arrsuitable ied a tota platform l of 113,0 for 00 an tonemer s of c gency onden rs esponse ate. Conmission. densate is a highly toxic and volatile chemical substance, and there is a risk of deflagration at any time after it Unmanned meant it could be deployed for a longer time, therefore widening the operational window. Most leaks.importantly Therefore, ,ithe t is use too of dathe ngeUSVs rous fro esolved r humathe ns tsecurity o enter tchallenge he core arof easurveying of the accin ide danger nt to p ous erfo ar rm eas. a mission. We urgently needed a mobile unmanned platform to replace humans in the core area of the In recent years, USVs have been widely researched and applied in a lot of fields [1]. Some new USVs are constantly accident to developed, obtain the such nece as ss‘Spartan ary inforScout’ mation designed , such as by th the e su USV bma team rine in top San ogrDiego aphy, [t2 h ], e ‘Nighthawk’ state of the shipwreck, the location of oil spills, and the situation of water pollution. from AAC (Accurate Automation Corp) [3], and a range of USVs from ASV(The Company of Autonomous Unmann Surface ed surV fa echile), ce vehsuch icles as (U the SVUSVs s) are that the called suita ‘C-WORKER’ ble platformand for‘C-T an ARGET’ emergen [4 c]. y Although response mission. Unmanned meant it could be deployed for a longer time, therefore widening the USVs have many applications at this stage, they are limited to carrying out missions for scientific r o esear perat ch, ionsuch al wias ndo envir w. M onmental ost impomonitoring rtantly, the [u 5– se 7 ],of envir the onmental USVs reso sampling lved the [s 8e,c 9u ],ri communication ty challenge of surveying in dangerous areas. In recent years, USVs have been widely researched and applied in a platform [10,11], and harbor protection and patrol [12–15]. However, emergency response mission for lot disaster of fields or [1]accident . Some ne ar w e U performed SVs are co by nstAUV(Autonomous antly developed, suUnderwater ch as ‘SpartaV nehicle) Scout’ or deROV(Remote signed by the USV team in San Diego [2], ‘Nighthawk’ from AAC (Accurate Automation Corp)[3], and a range of Operated Vehicle), for example, Kukulya, A.L. et al. developed an AUV-based approach inspired by USan Vs existing from AS small, V(Thelong-range Company system, of Auto called nomou the s ST u ethys rface Long-Range Vechile), suc AUV h as (LRAUV), the USVs in tha or t der calle to d ‘C-WORKER’ and ‘C-TARGET’ [4]. Although USVs have many applications at this stage, they are support the Arctic Doman Awareness Center (ADAC) for spill preparedness [16]. Valentine, M.M. et al. used limite rd emote-contr to carryinolled g outvehicles missionto s fquantify or scienti lar ficge reanimals search, s at uc five h as study envirsites onmto ent determine al monitor the inge [5ects –7], environmental sampling [8–9], communication platform [10–11], and harbor protection and patrol of the spill on deep-water animals [17].The only application of USVs for disaster was responding to Hurricane [12–15]. HW ow ilma. ever,During emerge the ncy r escue respo mission, nse misthe sionCenter for dfor isas Robot-Assisted ter or accidenSear t arch e p and erfoRescue rmed b at y AUV(Autonomous Underwater Vehicle) or ROV(Remote Operated Vehicle), for example, Kukulya the University of South Florida used a USV that called ‘AEOS-1’ to inspect docks and seawalls then bridges A L et a [18 l. ]. developed an AUV-based approach inspired by an existing small, long-range system, called the Tethys Long-Range AUV (LRAUV), in order to support the Arctic Doman Awareness In this emergency response mission, we deployed a newly designed USV. Compared with the pr Ce evious nter (A USVs, DAC) (1) fothe r sp impr ill poved reparnavigation edness[16].contr Valeol ntalgorithms ine M M et(path al. us following ed remotand e-con collision trolled avoidance) vehicles to quantify large animals at five study sites to determine the effects of the spill on deep-water can provide high navigation accuracy while ensuring the navigation safety; (2) the improved LARS animals[17].The only application of USVs for disaster was responding to Hurricane Wilma. During (Launch And Recovery System) enabled the USV to be quickly deployed and recovered in the mission the rescue mission, the Center for Robot-Assisted Search and Rescue at the University of South area; and (3) a new pump sampling system, which is small in size and light in weight, can be installed Florida used a USV that called ‘AEOS-1′ to inspect docks and seawalls then bridges [18]. or removed at any time. In this emergency response mission, we deployed a newly designed USV. Compared with the The rest of this paper is organized according to the structure below. In Section 2, we introduce the previous USVs, (1) the improved navigation control algorithms (path following and collision system architecture of the USV. The approach is proposed in Section 3. In Section 4, we introduce the avoidance) can provide high navigation accuracy while ensuring the navigation safety; (2) the mission process and analyze the mission data. Finally, the conclusion is given in Section 5. improved LARS (Launch And Recovery System) enabled the USV to be quickly deployed and recovered in the mission area; and (3) a new pump sampling system, which is small in size and light in weight, can be installed or removed at any time. Appl. Sci. 2020, 10, x FOR PEER REVIEW 3 of 21 Appl. Sci. 2020, 10, x FOR PEER REVIEW 3 of 21 TT hh ee r r ee ss t to o f ft h th is is p p aa pp ee rr i s is o o rr gg aa nn iz iz ee dd a a cc cc oo rr dd in in gg t o to t h th ee s s tr tr uu cc tu tu rr ee b b ee lo lo w w . .I n In S S ee cc tito io nn 2 2 , ,w w ee i n in tr tr oo dd uu cc ee th th ee s s yy ss te te m m a a rr cc hh itie te cc tu tu rr ee o o f ft h th ee U U SS V V . .T T hh ee a a pp pp rr oo aa cc hh i s is p p rr oo pp oo ss ee dd i n in S S ee cc tito io nn 3 3 . .I n In S S ee cc tito io nn 4 4 , ,w w ee i n in tr tr oo dd uu cc ee Appl. Sci. 2020, 10, 2704 3 of 21 th th ee m m is is ss io io nn p p rr oo cc ee ss ss a a nn dd a a nn aa ly ly zz ee t h th ee m m is is ss io io nn d d aa ta ta . .F F in in aa llly ly , ,t h th ee c c oo nn cc lu lu ss io io nn i s is g g iv iv ee nn i n in S S ee cc tito io nn 5 5 . . 2 2. 2 . .U USV U SS V V S System S yy ss te te m m S Structure S tr tu ru cc tu tu re re O Our O uu rr USV U U SS V V consisted cc oo nn ss is is te te d of d the oo f f following th th ee fo fo lllo lo w parts: w in in gg p Hull, p aa rr ts ts : :contr H H uu llol l,l , module, cc oo nn tr tr oo l l locomotion m m oo dd uu le le , , lo lo c module, c oo m m oo tito io n navigation n m m oo dd uu le le , , n module, n aa vv ig ig aa tito io and nn m m o mission o dd uu le le , ,a a n module. n dd m m is is ss io io Each nn m m oo of dd uu the le le . .E parts E aa cc hh o will o f ft h th e be e p p a discussed a rr ts ts w w ilill lb b e in e d d turn. is is cc uu ss s Figur s ee dd i n in e t 2 u tu r is r nn .an .F F ig overview ig uu rr ee 2 2 i s is a of a nn o the o vv ee r USV’s r vv ie ie w w o ar o f ft chitectur h th ee U U SS V V ’e. s ’s a a rr cc hh itie te cc tu tu rr ee . . U US SV V Navigation module Disel Navigation module Disel Engine Engine Fo Fro w ra wra d r d LiDAR CCD LiDAR CCD GPS RR ad aa d rar IN IS NS GPS looking sonar looking sonar Cammer Cammer W W ata et re -r je -j te t propulsion propulsion Acquisition construction Environment information Acquisition construction Environment information Bo Bto to ttm om co cn otn rt orlo b l o bx ox DD ies ie es le l MM oto io tin o n MM oto io tin o n MM aia ni n co cn otn rt orlo le ll rer geg n ee n re arta otror C C oo nn tr tr oo l l information cocn osn tr st u rc u tc io tin on information m m oo dd uu le le Acquisition construction Mission information Acquisition construction Mission information Fu Fe u le tla tn ak nk Multi-beam La Lu an uc n h c h a n ad n d Multi-beam AA DC DP CP SA SS AS Single- Sa Sm am plp in lig n g Single- SiS die d s ec s acn a n rer ce ocv oev re yr y ba bta hty hm ym ete rt yry beam device beam sosn oa nrar device de d veiv ci ece ba bta hty hm ym ete rt yry Ba Bta te tt re yry Sc S acn an nin nig n g de d veiv ci ece L L oo cc oo m m oo tito io nn M M is is ss io io nn m m oo dd uu le le module module F Figure F ig ig uu re re 2 2. 2 . .U Unmanned U nn m m aa nn nn ee dd s surface s uu rf ra fa cc ee v vehicle v ee hh ic ic le le ( (USV) U (U SS V V ) )a ar a rc r chitectur c hh itie te cc tu tu re r ee o overview o vv ee rv rv ie ie w w .. . 2.1. Hull Design 2.1. Hull Design 2.1. Hull Design The USV weighed 2300 kg and was 6.28 m 0.98 m 0.32 m (length width height) with a TT hh ee U U SS V V w w ee ig ig hh ee dd 2 2 33 00 00 k k gg a a nn dd w w aa ss 6 6 .2 .2 88 m m × × 0 0 .9 .9 88 m m × × 0 0 .3 .3 22 m m ( l(e le nn gg th th × × w w id id th th × × h h ee ig ig hh t) t )w w itih th a a maximum payload of 1 ton. The hull was divided into three compartments. Forward-looking sonar maximum payload of 1 ton. The hull was divided into three compartments. Forward-looking sonar maximum payload of 1 ton. The hull was divided into three compartments. Forward-looking sonar was installed at the front section. In consideration of vibration problems, an instrument cabinet which w w aa ss in in ss ta ta llle le dd aa t t th th ee fr fr oo nn t t ss ee cc tito io nn . . In In cc oo nn ss id id ee rr aa tito io nn oo f f vv ib ib rr aa tito io nn pp rr oo bb le le m m ss , , aa nn in in ss tr tr uu m m ee nn t t cc aa bb in in ee t t elastically connected with the deck was located in the middle section. On the other hand, a circulating w w hh ic ic hh e e la la ss titc ic aa llly ly c c oo nn nn ee cc te te dd w w itih th t h th ee d d ee cc kk w w aa ss l o lo cc aa te te dd i n in t h th ee m m id id dd le le s s ee cc tito io nn . .O O nn t h th ee o o th th ee rr h h aa nn dd , ,a a cooling system can prevent the instrument cabinet from overheating. Inboard diesel engine, fuel tank, cc ir ir cc uu la la titn in gg cc oo oo liln in gg ss yy ss te te m m cc aa nn pp rr ee vv ee nn t t th th ee in in ss tr tr uu m m ee nn t t cc aa bb in in ee t t fr fr oo m m oo vv ee rr hh ee aa titn in gg . . In In bb oo aa rr dd dd ie ie ss ee l l battery, and water-jet propulsion were installed in the tail section. The installation location of each ee nn gg in in ee , ,f u fu ee l lt a ta nn kk , ,b b aa tt te te rr yy , ,a a nn dd w w aa te te rr -j-e je t tp p rr oo pp uu ls ls io io nn w w ee rr ee i n in ss ta ta llle le dd i n in t h th ee t a ta ili ls s ee cc tito io nn . .T T hh ee i n in ss ta ta llla la tito io nn device is shown in Figure 3. lo lo cc aa tito io nn o o f fe e aa cc hh d d ee vv ic ic ee i s is s s hh oo w w nn i n in F F ig ig uu rr ee 3 3 . . Figure 3. Device installation location. Appl. Sci. 2020, 10, x FOR PEER REVIEW 4 of 21 Figure 3. Device installation location. Appl. Sci. 2020, 10, 2704 4 of 21 2.2. Control Module 2.2. Control Module The control module can collect sensor information in real-time, control the USV’s movement, manage the mission device, and realize the independent work of the USV. The control module The control module can collect sensor information in real-time, control the USV’s movement, consisted of an industrial personal computer (IPC) and a bottom control box which was equivalent manage the mission device, and realize the independent work of the USV. The control module consisted to the brain of the USV. The environmental information, the ontology information, and the target of an industrial personal computer (IPC) and a bottom control box which was equivalent to the brain information collected by the sensors were transmitted to the control module. The control algorithms of the USV. The environmental information, the ontology information, and the target information pre-embedded in the IPC processed this information and then different control instructions were collected by the sensors were transmitted to the control module. The control algorithms pre-embedded calculated and transmitted to other modules. in the IPC processed this information and then dierent control instructions were calculated and The key of the control module was the IPC interfaced with a serial extension board (Digital transmitted to other modules. Signal Processor) and a network switch. The general IPC from YanHua’s APAX series was used as a The key of the control module was the IPC interfaced with a serial extension board (Digital Signal hardware platform and the embedded control system based on Linux was developed. Since data Processor) and a network switch. The general IPC from YanHua’s APAX series was used as a hardware could be collected, processed, and stored independently by the IPC, the loss of the data could be platform and the embedded control system based on Linux was developed. Since data could be effectively avoided in the case of communication interruption or indirect/incomplete transmission. collected, processed, and stored independently by the IPC, the loss of the data could be eectively avoided in the case of communication interruption or indirect/incomplete transmission. 2.3. Locomotion Module 2.3. Locomotion Module The locomotion module was the execution module of our USV. After receiving the control instructions, it drove the USV to perform various actions. Diesel engine, diesel generator, water-jet The locomotion module was the execution module of our USV. After receiving the control propeller, fuel tank, and battery constituted the locomotion module. It is worth mentioning that instructions, it drove the USV to perform various actions. Diesel engine, diesel generator, water-jet traditional propeller propulsion was replaced by a water-jet propulsion. Better working ability and propeller, fuel tank, and battery constituted the locomotion module. It is worth mentioning that maneuverability in the shallow water, higher thrust, and lower noise were the obvious advantages traditional propeller propulsion was replaced by a water-jet propulsion. Better working ability and of water-jet propulsion technology over propeller propulsion [19–20]. The locomotion module maneuverability in the shallow water, higher thrust, and lower noise were the obvious advantages of ensured that the maximum speed of the USV was no less than 13 kn(Knot), the cruising speed was water-jet propulsion technology over propeller propulsion [19,20]. The locomotion module ensured about 10 kn, and the ranges of working speed were 4 to 8 kn. The USV could run for about 5 h at that the maximum speed of the USV was no less than 13 kn(Knot), the cruising speed was about 10 kn, cruising speed and 12 h at working speed. and the ranges of working speed were 4 to 8 kn. The USV could run for about 5 h at cruising speed and 12 h at working speed. 2.4. Navigation Module 2.4. Navigation Module The navigation module received data from sensors such as GPS(Global Positioning System), The navigation module received data from sensors such as GPS(Global Positioning System), INS(Inertial Navigation System), compass, forward looking sonar, radar, and LiDAR(Light INS(Inertial DetectioNavigation n and Rang System), ing), etccompass, . After ge forwar tting td he looking sensorsonar data,, radar the n , a and viga LiDAR(Light tion module Detection analyzed the and Ranging), etc. After getting the sensor data, the navigation module analyzed the USV’s position, USV's position, speed, heading, and obstacle information, and gave the USV's next speed and speed, hea heading, ding com and binobstacle ed with t information, he mission rand equigave remen the ts. USV’s If obstnext aclesspeed existeand d, thheading e speed a combined nd headin with g had to the mission requirements. If obstacles existed, the speed and heading had to be adjusted through the be adjusted through the corresponding collision avoidance algorithm. The architecture of the corresponding navigation collision module iavoidance s shown inalgorithm. Figure 4. The architecture of the navigation module is shown in Figure 4. Navigation Sensor data module Obstacle Location Mission Information information requirements Obstacle Path detection following algorithm Initial speed Initial heading Collision Speed avoidance algorithm Heading Figure 4. Navigation module. Figure 4. Navigation module. Appl. Sci. 2020, 10, 2704 5 of 21 Appl. Sci. 2020, 10, x FOR PEER REVIEW 5 of 21 2.5. Mission Module 2.5. Mission Module T The he mission missionmodule modulwas e wa divided s dividinto ed ithr ntoee th systems: ree systScanning, ems: Scansampling, ning, samand plinLARS. g, andThe LAscanning RS. The system mainly used the device to realize the underwater exploration. The sampling system was scanning system mainly used the device to realize the underwater exploration. The sampling system w designed as design to ed collect to colwater lect wa samples ter samp in ler seal in r time. eal tim LARS e. LA was RS w used as us to ed deploy to depl and oy arn ecover d recov the er t USV he Uin SVthe in mission area. the mission area. 3. Approach 3. Approach 3.1. Path Following Algorithm 3.1. Path Following Algorithm A straight path following algorithm based on the predicted position control was adopted in our A straight path following algorithm based on the predicted position control was adopted in our 0 0 USV. The core idea of the algorithm was to calculate the d (the USV’s predicted lateral oset). If d was USV. The core idea of the algorithm was to calculate the ’(the USV’s predicted lateral offset). If ’ larger, the angle which made the USV return to the planned path was also greater. was larger, the angle which made the USV return to the planned path was also greater. The schematic diagram of the algorithm is shown in Figure 5. We defined some variables, where The schematic diagram of the algorithm is shown in Figure 5. We defined some variables, Yaw and Angel represent the course angle and turning angle required for the USV to return to the where and represent the course angle and turning angle required for the USV to return planned path, and d and d represent the actual lateral oset and predicted lateral oset, respectively. to the planned path, and and ’ represent the actual lateral offset and predicted lateral offset, The calculation formula of d is Equation (3). The calculation formula of d is Equation (2), where the respectively. The calculation formula of is Equation (3). The calculation formula of ’ is Equation linear speed and angular speed of the USV were set to V and ! . Yaw and Angel are calculated usv usv (2), where the linear speed and angular speed of the USV were set to and ω . and usv as Equation (1), where TogestDist and ToDestAng are the distance and angle from the USV to the are calculated as Equation (1), where and are the distance and angle from terminating waypoint, and ' is the heading angle of the USV. PathAng is the angle of the path, which is the USV to the terminating waypoint, and is the heading angle of the USV. ℎ is the angle calculated from the start and end waypoint of the path. ToDestDist and ToDestAng are calculated based of the path, which is calculated from the start and end waypoint of the path. and on the USV’s state (position, heading angle, the latitude and longitude information to the terminating are calculated based on the USV’s state (position, heading angle, the latitude and waypoint, etc.). Parameters T and T are called time-lag constant and time-lag slope, respectively. The 1 2 longitude information to the terminating waypoint, etc.). Parameters and are called time-lag f(x) is a saturation function, in order to modify the distance conversion coecient into a variable constant and time-lag slope, respectively. The ( ) is a saturation function, in order to modify the form. Therefore, both the real time and smoothness of the USV movement are considered. distance conversion coefficient into a variable form. Therefore, both the real time and smoothness of the USV movement are considered. 0 0 Yaw = ToDestAng + f(d ) Angel = ToDestAng + f(d ) ' (1) d d ( ) (1) = + ( ’) × = + ’ × − d = d + V T sin(PathAng ! T ) (2) usv 1 usv 2 ’ = + × × ( ℎ − × ) (2) d = ToDestDist sin (PathAng ToDestAng) (3) (3) = × × ( ℎ − ) 60.0x 60.0 f(x) = (4) 0.5(jxj 10) ( ) = (4) jxj 1 + e . (| | ) | |(1 + ) Figure 5. Path-following algorithm based on predicted position control. Figure 5. Path-following algorithm based on predicted position control. In order to calculate and , , , and are the three parameters that must be calculated, so we focused on how to determine these parameters. Appl. Sci. 2020, 10, 2704 6 of 21 In order to calculate Yaw and Angel, T , T , and are the three parameters that must be calculated, 1 2 d so we focused on how to determine these parameters. Time-lag constant T : Parameter T acting on V was mainly used to calculate d . According 1 1 usv to the results of the sea trials, when the USV had a set throttle value of 500, T = 5 could make the algorithm achieve a higher control accuracy. When the throttle value increased, the T decreased accordingly. Table 1 shows the T for each throttle setting. Table 1. Selection of T for each throttle value. Throttle Value 300 400 500 600 700 800 Time delay constant T 6 5.5 5 5 3.5 2 Time-lag slope T : Parameter T acting on ! was related to the sea states during navigation. 2 2 usv According to the results of the sea trials, it was appropriate to set the T to 5 when the sea states were 1–2. When the sea state was 3, it was appropriate to set the T to 5.5 or more. This is because the USV was more dicult to turn in poor sea states, therefore, it was necessary to give a long forecast value when calculating d . Distance conversion coecient : limits the values of Yaw and Angel. This parameter was d d generally set to 2~3. According to the results of the sea trials, = 3 was a suitable value. If set to 3, the maximum control amount of the angle was 60 . 3.2. Collision Avoidance Algorithm The control of the collision avoidance for USVs is generally divided into two layers [21]. The first layer is global collision avoidance, which is to construct a proper environment model based on the information of known obstacles or danger areas and then plan a safe path. The second layer is the short-range real-time collision avoidance based on the real-time sensor information, which enables USVs to quickly avoid the obstacle that appears suddenly in the surrounding environment. Therefore, short-range real-time collision avoidance is the last line of defense to ensure the safety of USVs. Velocity obstacle (VO) algorithm is a kind of short-range real-time collision avoidance algorithm commonly used in USVs. However, the traditional VO algorithm does not consider the influence of the kinematic performance of USVs and the error of obstacle movement information, nor does it specify when to start collision avoidance and when to complete. Therefore, in order to overcome these problems, we combined a dynamic window algorithm with elliptic VO algorithm, gave the judgment conditions for when to start and end collision avoidance, and used the virtual obstacle method to reduce the influence of the error of obstacle movement information. 3.2.1. Elliptic VO Algorithm The basic principle of VO algorithm was introduced in detail in [22], and the key dierence between the elliptic VO algorithm and the VO algorithm is the process of solving the tangent. In the VO algorithm, if you want to judge whether a USV will collide with an obstacle, you must require two tangent lines of the obstacle relative to the USV. As shown in Figure 6, in order to find the tangent lines of elliptical obstacle conveniently, a body-fixed coordinate system and an obstacle coordinate system was established. The xOy is the 0 0 0 body-fixed coordinate system of the USV and x O y is the obstacle coordinate system. The red ellipse is an obstacle and the green ellipse is an USV, which was simplified as a particle. Point O is the center of the USV. O is the center of the obstacle. If the coordinates of the USV in the body-fixed coordinate system are USV = [0, 0] , the coordinates of the USV in the obstacle coordinate system are: boat USV = R (USV C) (5) obs boat Appl. Sci. 2020, 10, 2704 7 of 21 where C is the coordinate of the center point of the obstacle in the body-fixed coordinate system and R is the rotation matrix. " # Appl. Sci. 2020, 10, x FOR PEER REVIEW cos sin 7 of 21 R = (6) sin cos When the coordinates of the USV in the obstacle coordinate system are obtained, the tangent When the coordinates of the USV in the obstacle coordinate system are obtained, the tangent coordinate ( , ) in the obstacle coordinate system can be obtained by Equation (7) ( 1 and ( ) coordinate x , y in the obstacle coordinate system can be obtained by Equation (7) (T1 and T2 T T obs obs 2 in Figure 6): in Figure 6): 2 2 > a y > T T + = 1 + = 1 < 2 2 a b (7) > (7) > x m y n + = 1, 2 2 a b + = 1, Then, T1 , T2 is converted into the body-fixed coordinate system by using Equation (8): obs obs Then, 1 , 2 is converted into the body-fixed coordinate system by using Equation (8): T = RT + C (8) boat obs = + (8) Figure 6. Ellipse tangents. Figure 6. Ellipse tangents. 3.2.2. VO Algorithm Based on Dynamic Window Algorithm 3.2.2. VO Algorithm Based on Dynamic Window Algorithm After calculating the colliding VO sets by elliptic VO algorithm, the data in the non-VO sets were After calculating the colliding VO sets by elliptic VO algorithm, the data in the non-VO sets the optional collision avoidance velocity vectors for the USV. However, due to the constraint of the were the optional collision avoidance velocity vectors for the USV. However, due to the constraint of dynamic performance of the USV, many velocity vectors in the non-VO sets were inaccessible to the the dynamic performance of the USV, many velocity vectors in the non-VO sets were inaccessible to USV. The dynamic window algorithm considered the kinematic performance of the USV [20], and only the USV. The dynamic window algorithm considered the kinematic performance of the USV [20], calculated the moving velocity that the USV can reach within a given time window Dt, that is, the and only calculated the moving velocity that the USV can reach within a given time window ∆ , that velocity window v : is, the velocity window : n h io . . v = v v 2 v vDt, v + vDt (9) c c = | ∈ − ∆ , + ∆ (9) and the angular velocity that can be achieved, that is, the angular velocity window ! : and the angular velocity that can be achieved, that is, the angular velocity window : n h io . . ! = ! ! 2 ! !Dt,! + !Dt (10) = | ∈ − ∆ , + c ∆ c (10) In Equation (9), is the current moving speed of the USV and is the acceleration of the In Equation (9), v is the current moving speed of the USV and v is the acceleration of the USV. USV. In Equation (10), is the current angular velocity of t.he USV and is the angular In Equation (10), ! is the current angular velocity of the USV and ! is the angular acceleration of the acceleration of the USV. According to Equation (11), the heading angle that the USV can get within USV. According to Equation (11), the heading angle that the USV can get within Dt can be calculated: ∆ can be calculated: 1 . 1 . 1 1 2 2 = 2 + ! Dt !Dt , + ! Dt + !Dt (1(11) 1) = ∈ + ∆ − ∆ c , + ∆ + c ∆ d h h 2 2 2 2 where is the current heading of the USV. where is the current heading of the USV. Through the Equations (9) and (11), and can be determined, but the elements in sets of Through the Equations (9) and (11), v and can be determined, but the elements in sets of v and d d d and are continuous, which is not conducive to calculation in engineering. Therefore, is are continuous, which is not conducive to calculation in engineering. Therefore, v is discretized d d discretized into speeds and is discretized into heading directions. Each discretized into M speeds and is discretized into N heading directions. Each discretized velocity v and heading d i velocity and heading form a velocity vector ( , ) , and then there are × velocity vectors. The set of velocity vectors is called reachable velocity (RV). The velocity vectors satisfying Equation (9) in the RV set will collide with the obstacle. Excluding these velocity vectors from the RV set can obtain a safe set of velocity vectors, called reachable avoidance velocity (RAV): = | ∈ , ∉ (12) Appl. Sci. 2020, 10, 2704 8 of 21 form a velocity vector (v , ), and then there are M N velocity vectors. The set of velocity vectors i i i is called reachable velocity (RV). The velocity vectors satisfying Equation (9) in the RV set will collide with the obstacle. Excluding these velocity vectors from the RV set can obtain a safe set of velocity vectors, called reachable avoidance velocity (RAV): RAV = fVjV 2 RV, V < VOg (12) Appl. Sci. 2020, 10, x FOR PEER REVIEW 8 of 21 As shown in Figure 7, the red area is VO area, the intersection of RV and VO is the velocity vector As shown in Figure 7, the red area is VO area, the intersection of RV and VO is the velocity where collision will occur, and the RAV part is the safe velocity vector. vector where collision will occur, and the RAV part is the safe velocity vector. Figure 7. RV(Reachable Velocity)and RAV (Reachable Avoidance Velocity). Figure 7. RV(Reachable Velocity)and RAV (Reachable Avoidance Velocity). After obtaining the RAV, it was necessary to select the appropriate velocity vector in the RAV After obtaining the RAV, it was necessary to select the appropriate velocity vector in the RAV accor according ding to tothe themission mission r equir requements. irementsIn . In di der iffent eren missions, t mission ther s, th eear re e a di re er dient fferselection ent selectcriteria, ion crite and ria, the following evaluation formula was used to select in this mission: and the following evaluation formula was used to select in this mission: (13) G = (13) ij ‖( cos − cos , sin − sin )‖ jj(v cos v cos , v sin v sin )jj c h i i c h i i where v is the current speed of the USV, is the current heading of the USV, (v , ) is a certain c i i where is the current speed of the USV, is the current heading of the USV, ( , ) is a certain velocity vector in RAV, and (v , ), which can maximize G , is taken as the velocity vector for the USV i i ij velocity vector in RAV, and ( , ), which can maximize , is taken as the velocity vector for the to avoid the obstacle. Once a velocity vector is selected, the USV will always travel along this speed USV to avoid the obstacle. Once a velocity vector is selected, the USV will always travel along this vector until there are new dangerous situations or the obstacle is completely avoided. speed vector until there are new dangerous situations or the obstacle is completely avoided. 3.2.3. Starting Collision Avoidance 3.2.3. Starting Collision Avoidance When judging whether the USV will collide with an obstacle, the distance between the USV and When judging whether the USV will collide with an obstacle, the distance between the USV and the obstacle is the smallest at the collision time, and their respective positions are called CPA(Close the obstacle is the smallest at the collision time, and their respective positions are called CPA(Close Point Approach). The time required for the USV to reach its CPA point is called t . As shown CPA Point Approach). The time required for the USV to reach its CPA point is called . As shown in in Figure 8, the red and green solid ellipses are the positions of the obstacle and USV at the time t , Figure 8, the red and green solid ellipses are the positions of the obstacle and USV at the time , V and V are the velocity vectors of the obstacle and USV at time t , the red and green dashed usv obs 0 and are the velocity vectors of the obstacle and USV at time , the red and green dashed ellipses are the positions of the obstacle and USV at time t , and the CPA and CPA points are CPA obs USV ellipses are the positions of the obstacle and USV at time , and the and points the positions of the center points of the obstacle and USV at time t . The t is calculated from CPA CPA are the positions of the center points of the obstacle and USV at time . The is calculated Equation (14): from Equation (14): (P P )(V V ) USV obs USV obs t = (14) CPA ( − )( − ) 2 jj(V V )jj USV obs = (14) ‖( − ‖ Appl. Sci. 2020, 10, x FOR PEER REVIEW 8 of 21 As shown in Figure 7, the red area is VO area, the intersection of RV and VO is the velocity vector where collision will occur, and the RAV part is the safe velocity vector. Figure 7. RV(Reachable Velocity)and RAV (Reachable Avoidance Velocity). After obtaining the RAV, it was necessary to select the appropriate velocity vector in the RAV according to the mission requirements. In different missions, there are different selection criteria, and the following evaluation formula was used to select in this mission: = (13) ‖( cos − cos , sin − sin )‖ where is the current speed of the USV, is the current heading of the USV, ( , ) is a certain velocity vector in RAV, and ( , ), which can maximize , is taken as the velocity vector for the USV to avoid the obstacle. Once a velocity vector is selected, the USV will always travel along this speed vector until there are new dangerous situations or the obstacle is completely avoided. 3.2.3. Starting Collision Avoidance When judging whether the USV will collide with an obstacle, the distance between the USV and the obstacle is the smallest at the collision time, and their respective positions are called CPA(Close Point Approach). The time required for the USV to reach its CPA point is called . As shown in Figure 8, the red and green solid ellipses are the positions of the obstacle and USV at the time , and are the velocity vectors of the obstacle and USV at time , the red and green dashed ellipses are the positions of the obstacle and USV at time , and the and points are the positions of the center points of the obstacle and USV at time . The is calculated from Equation (14): ( − )( − ) = (14) ‖ ‖ Appl. Sci. 2020, 10, 2704 ( − 9 of 21 Figure 8. Close point approach and start avoidance point. Assuming that the speed of the USV is kept constant, i.e., the USV can turn at a constant angular acceleration. In Figure 8, in the process of sailing to CPA point, the USV turns left with a constant USV angular acceleration at point B, which is tangent to the obstacle at point P and just along the path B P . The time required for the USV to sail from point B to point P is t . Then the USV starts to turn L L L left to avoid the obstacle at the time t = t , which is just tangent to the obstacle at point P . P is CPA L L L calculated from Equation (15): 8 R 1 2 > x = x + v cos + ! t + t dt B 0 0 > 2 (15) y = y + v sin + ! t + t dt > B 0 0 0 2 P C + P C = 2a, L 1 L 2 where (x, y), (x , y ) are the coordinates of point P and point B in the obstacle coordinate system, B B L respectively , and v, , ! and are the current velocity, heading, angular velocity, and angular 0 0 acceleration of the USV, respectively. P C + P C is the sum of the distances from P to the ellipse L 1 L L in the obstacle coordinate system. The a is the semimajor axis of the ellipse. The USV turning right is similar to turning left. The time of starting collision avoidance is t that can be calculated by avoid Equation (16): t = kmax(t , t ) (16) avoid L R where k is a coecient that is greater than 1 to ensure the safety and smooth turning of the USV. When t = t , the USV starts to avoid the obstacle. CPA avoid 3.2.4. Ending Collision Avoidance In this algorithm, the USV needs to travel to the destination along the planned path, therefore, collision avoidance can be ended as long as the USV meets the requirements: V < VO and V < VO (17) LOS dest In Equation (17), V is the velocity vector planned for path following and V is the velocity LOS dest vector when the USV sails to the target point. 3.2.5. Virtual Obstacle The VO algorithm is set to fully know the obstacle motion information. However, in the actual navigation process, the motion information of the obstacle obtained by the sensor had errors (our USV used LiDAR as the collision avoidance sensor). These errors can cause the USV to collide with the obstacle and, therefore, need to be considered. Appl. Sci. 2020, 10, 2704 10 of 21 Assuming that the velocity vector of the obstacle obtained by the sensor is V and the error set of the velocity vector of the obstacle is V , the actual velocity vector set of the obstacle is: V = V V (18) P t E where is a Minkowski vector sum operation. Assuming that each element in the V is a velocity vector of a virtual obstacle, and the position and size of the virtual obstacle are the same as the original obstacle, the velocity vector of the virtual obstacle is: V = V + V, V 2 V (19) V t P Find the VO set of the obstacle and its associated virtual obstacle and this set is the final VO set of the obstacle. The flowchart of the short-range real-time collision avoidance algorithm is shown in Figure 9. Figure 9. The flowchart of the short-range real-time collision avoidance algorithm. Figure 9. The flowchart of the short-range real-time collision avoidance algorithm. 3.3. LARS The mothership carrying out this mission was equipped with a davit type of LARS. Based on this LARS, we developed a special automatic docking device that solved the problems of docking between our USV and the LARS, thereby improving the accuracy and eciency of deployment and recovery. Traditional docking devices use a rubber band to eject a rope onto the mothership, and it is necessary to manually reset the rubber band after each ejection, which is cumbersome and dangerous. The use of the rubber band is limited, especially in the environment of high temperature and humidity. Therefore, it has to replace the rubber band frequently, which greatly increases the cost of use. In addition, the elastic force of the rubber band is fixed and the ejection distance is inconvenient to adjust. The newly designed device used an ejection mechanism of the high-pressure gas type instead of the rubber band, which could flexibly change the ejection distance by adjusting the pressure of the compressed air and automatically inflating after each ejection. Compared with the previous ejection mechanism, the new ejection mechanism greatly improved the accuracy, safety, and flexibility of the whole system. The distance of the minimum ejection was 10 m, the distance of the maximum ejection was 100 m, and the inflation time was less than 5 s. The device had both automatic and manual modes. Appl. Sci. 2020, 10, 2704 11 of 21 When in the automatic mode, the USV automatically judged the relative position with the mothership, according to the GPS information, adjusted the ejection parameters, and completed ejection. When in the manual mode, the operator can adjust the ejection parameters of the device through the console on the mothership. In practical applications, the device can safely and quickly deploy or recover 3 tons of USV (7.5 m length) under the sea state 4. As shown in Figure 10, there were three parts in the docking device: (1) The ejection mechanism: The lead and gas cannon were ejected from the USV. (2) The PTZ (Pan/Tilt/Zoom) mechanism: Adjust the launching attitude of the ejection mechanism to ensure that the gas cannon and lead can be launched to the mother ship. The PTZ structure can be adjusted between 0–70 and 0–180 in the pitch and horizontal directions. (3) The docking mechanism: The interface between the USV and the mothership, which realized the lifting of the USV. As shown in Table 2, according to the results of the sea trials, we measured the flying height and time of the gas cannon when the ejection mechanism launched at dierent initial angles. Appl. Sci. 2020, 10, x FOR PEER REVIEW 11 of 21 (a) (b) Figure 10. Docking device (a) Architectural overview of the docking device. (b) Composition of the Figure 10. Docking device (a) Architectural overview of the docking device. (b) Composition of the docking device. docking device. Table 2. The test results of the ejection mechanism. We focused on the recovery process because the deployment process was simple and warranted 30 35 40 45 50 55 60 no further discussion. The recovery process is shown in Figure 11 (in the automatic mode). Step (1): Height(m) 7.02 8.72 10.53 12.35 15.03 17.02 19.54 The USV sails to the vicinity of the mother ship, and the USV’s GPS information is transmitted to the Time (s) 0.93 0.98 1.06 1.15 1.26 1.42 1.61 IPC, which calculates the recovery parameters (gas pressure, PTZ mechanism angle, etc.) based on the relative positions of the USV and mothership. Step (2): Start the ejection mechanism and the lead We focused on the recovery process because the deployment process was simple and warranted and gas cannon are ejected to the deck of the mothership. Step (3): Slide the connector on the boom no further discussion. The recovery process is shown in Figure 11 (in the automatic mode). Step (1): of the mothership into the locking device through the lead. Step (4): When the sensor detects the The USV sails to the vicinity of the mother ship, and the USV’s GPS information is transmitted to the connector has fully entered the docking mechanism, the docking mechanism quickly locks the IPC, which calculates the recovery parameters (gas pressure, PTZ mechanism angle, etc.) based on the connector and then lifts the USV. relative positions of the USV and mothership. Step (2): Start the ejection mechanism and the lead and gas cannon are ejected to the deck of the mothership. Step (3): Slide the connector on the boom of the mothership into the locking device through the lead. Step (4): When the sensor detects the connector Step2 has fully entered Stethe p1 docking mechanism, the docking mechanism quickly locks the connector and then lifts the USV. (b) (a) Step4 Step3 (d) (c) Figure 11. Flow chart of the recovery process. (a) Step 1. (b) Step 2. (c) Step 3. (d) Step 4. Table 2. The test results of the ejection mechanism. Appl. Sci. 2020, 10, x FOR PEER REVIEW 11 of 21 (a) (b) Figure 10. Docking device (a) Architectural overview of the docking device. (b) Composition of the docking device. We focused on the recovery process because the deployment process was simple and warranted no further discussion. The recovery process is shown in Figure 11 (in the automatic mode). Step (1): The USV sails to the vicinity of the mother ship, and the USV’s GPS information is transmitted to the IPC, which calculates the recovery parameters (gas pressure, PTZ mechanism angle, etc.) based on the relative positions of the USV and mothership. Step (2): Start the ejection mechanism and the lead and gas cannon are ejected to the deck of the mothership. Step (3): Slide the connector on the boom of the mothership into the locking device through the lead. Step (4): When the sensor detects the Appl. Sci. 2020, 10, 2704 12 of 21 connector has fully entered the docking mechanism, the docking mechanism quickly locks the connector and then lifts the USV. Step2 Step1 (b) (a) Step4 Step3 (d) (c) Figure Figure11. 11. Flow Flow chart chart of of the ther r ecovery ecoverypr pr ocess. ocess. ((a a)) Step Step 1. 1. ((b b)) Step Step 2. 2. ( (c c) ) Step Step 3. 3. ( (d d) ) S Step tep 4 4.. 3.4. Sampling System Table 2. The test results of the ejection mechanism. We designed a pump sampling system for our USV, which used a high-precision quantitative peristaltic pump to pump water samples by alternately squeezing and releasing the flexible delivery hose. The delivery hose can be placed at dierent depths to obtain water samples from dierent layers. Compared with other types of pumps, the quantitative peristaltic pump did not directly contact the water samples and could precisely control the sampling rate. The maximum sampling rate of the system was 1200 mL/min, and the system could flexibly adjust the sampling rate in the range of 500 mL/min–1000 mL/min. The weight of the system was only 10 kg, the system was 0.3 m 0.2 m 0.5 m (length width height) and was directly installed on the deck of the USV, which could be removed at any time. In order to improve the reliability of the system, five independent pump sampling systems were installed on the USV. As shown in Figure 12, the system was composed of a peristaltic pump, an automatic retracting hose, and a friction wheel. When the USV received the instruction of the sampling, the friction wheel drove the hose into the water, and then the peristaltic pump alternately squeezed and released the flexible delivery hose to pump the fluid into the collecting box. Finally, when the sampling work was completed, the flexible delivery hose was recovered. Appl. Sci. 2020, 10, x FOR PEER REVIEW 12 of 21 θ 30° 35° 40° 45° 50° 55° 60° Height(m) 7.02 8.72 10.53 12.35 15.03 17.02 19.54 Time (s) 0.93 0.98 1.06 1.15 1.26 1.42 1.61 3.4. Sampling System We designed a pump sampling system for our USV, which used a high-precision quantitative peristaltic pump to pump water samples by alternately squeezing and releasing the flexible delivery hose. The delivery hose can be placed at different depths to obtain water samples from different layers. Compared with other types of pumps, the quantitative peristaltic pump did not directly contact the water samples and could precisely control the sampling rate. The maximum sampling rate of the system was 1200 mL/min, and the system could flexibly adjust the sampling rate in the range of 500 mL/min–1000 mL/min. The weight of the system was only 10 kg, the system was 0.3 m × 0.2 m × 0.5 m (length × width × height) and was directly installed on the deck of the USV, which could be removed at any time. In order to improve the reliability of the system, five independent pump sampling systems were installed on the USV. As shown in Figure 12, the system was composed of a peristaltic pump, an automatic retracting hose, and a friction wheel. When the USV received the instruction of the sampling, the friction wheel drove the hose into the water, and then the peristaltic pump alternately squeezed and released the flexible delivery hose to pump the fluid into the collecting box. Finally, when the sampling work was Appl. Sci. 2020, 10, 2704 13 of 21 completed, the flexible delivery hose was recovered. (b) (a) Figure 12. Sampling system (a) Architectural overview of the sampling system. (b) Composition of the Figure 12. Sampling system (a) Architectural overview of the sampling system. (b) Composition of sampling system. the sampling system. 4. Mission 4. Mission 4.1. Mission Plan 4.1. Mission Plan In this mission, our USV was required to cover the mission area with minimum cost and obtain the mission data. In order to ensure that the entire shipwreck could be scanned, according to the shape In this mission, our USV was required to cover the mission area with minimum cost and obtain data of the ‘Sanchi’, the direction of the wind, and the flow of the water, we determined a rectangular the mission data. In order to ensure that the entire shipwreck could be scanned, according to the mission area of 600 600 m based on the GPS information of the sinking position. shape data of the ‘Sanchi’, the direction of the wind, and the flow of the water, we determined a According to the mission area, the distribution information of obstacles (mainly the navigation rectangular mission area of 600×600 m based on the GPS information of the sinking position. mark of the accident area and the rescue buoys that were urgently placed after the accident) and the According to the mission area, the distribution information of obstacles (mainly the navigation scanning width of the USV, the mission area was modeled by the method of the scan-line fill. As shown mark of the accident area and the rescue buoys that were urgently placed after the accident) and the in Figure 13a, after the environment was modeled, the mission area was decomposed into a series of scanning width of the USV, the mission area was modeled by the method of the scan-line fill. As Appl. Sci. 2020, 10, x FOR PEER REVIEW 13 of 21 grids with attribute information, and the USV formed a path that completely covered the environment shown in Figure 13a, after the environment was modeled, the mission area was decomposed into a by successively selecting the next scan grid. Based on the rules of the maritime measurement, the series of grids with attribute information, and the USV formed a path that completely covered the measurement, the selection principle of the grid node was that of using the method of the global selection principle of the grid node was that of using the method of the global path planning with environment by successively selecting the next scan grid. Based on the rules of the maritime path planning with artificial initial path constraints. Figure 13b is the planned path of the USV for artificial initial path constraints. Figure 13b is the planned path of the USV for this mission. A total of this mission. A total of 9 lines were planned, each line was 440 m, and the distance between the lines 9 lines were planned, each line was 440 m, and the distance between the lines was 40 m. It is worth was 40 m. It is worth mentioning that when the USV worked according to the planned path, it could mentioning that when the USV worked according to the planned path, it could replan the mission replan the mission area according to the relative position of the shipwreck and the USV after finding area according to the relative position of the shipwreck and the USV after finding the shipwreck, thus the shipwreck, thus improving the work efficiency. improving the work eciency. (a) (b) Figure 13. (a) Environmental modeling. (b) The planned path of the mission. Figure 13. (a) Environmental modeling. (b) The planned path of the mission. 4.2. Mission Process On the morning of 15 January 2018, we received orders and boarded on the XianYangHong19 (mothership for our USV) to the accident area. After the mission, the Maritime Search and Rescue Center of Shanghai urgently designated an area with a radius of 10 nautical miles around the sinking position of the ‘Sanchi’. All nonrescue vessels were prohibited from entering this area. Figure 14 shows the specific process of the mission. Appl. Sci. 2020, 10, 2704 14 of 21 4.2. Mission Process On the morning of 15 January 2018, we received orders and boarded on the XianYangHong19 (mothership for our USV) to the accident area. After the mission, the Maritime Search and Rescue Center of Shanghai urgently designated an area with a radius of 10 nautical miles around the sinking position of the ‘Sanchi’. All nonrescue vessels were prohibited from entering this area. Figure 14 shows the specific process of the mission. Appl. Sci. 2020, 10, x FOR PEER REVIEW 14 of 21 Figure 14. The USV in the mission: (a) The USV was being deployed in the mission area. (b) The USV Figure 14. The USV in the mission: (a) The USV was being deployed in the mission area. (b) The USV was deployed successfully and sailed to the target. (c) The USV was scanning. (d) Display control was deployed successfully and sailed to the target. (c) The USV was scanning. (d) Display control interface on the mothership. (e) The USV was returning to the mothership. (f) The surface of the hull interface on the mothership. (e) The USV was returning to the mothership. (f) The surface of the hull after the mission was completed. after the mission was completed. At 8:20 on 18 January 2018, the USV was successfully deployed at the edge of the mission area. At 8:20 on 18 January 2018, the USV was successfully deployed at the edge of the mission area. On the day of the mission, the wind speed was 7.8 m/s, the wind direction was 32.5 , the temperature On the day of the mission, the wind speed was 7.8 m/s, the wind direction was 32.5°, the was 9.3 C, and the wave height was 1.2 m. At 8:30 the USV began to work along the planned paths. temperature was 9.3 °C, and the wave height was 1.2 m. At8:30 the USV began to work along the At 8:57, the ‘Sanchi’ oil tanker was found from the multibeam images. The images showed that planned paths. At 8:57, the ‘Sanchi’ oil tanker was found from the multibeam images. The images the ‘Sanchi’ oil tanker was located below the starboard of the USV and at the angle of 10 to the showed that the ‘Sanchi’ oil tanker was located below the starboard of the USV and at the angle of USV’s heading. We narrowed the scope of the mission area based on the preliminary scan results 10° to the USV’s heading. We narrowed the scope of the mission area based on the preliminary scan and replanned the path on the basis of the previously planned path. Three lines were added to the results and replanned the path on the basis of the previously planned path. Three lines were added north direction, at the same time, two north-south direction lines were added. The length of the to the north direction, at the same time, two north-south direction lines were added. The length of line was 380 m and the spacing was 270 m. The USV continued to work and then the full-precision the line was 380 m and the spacing was 270 m. The USV continued to work and then the multibeam images of the ‘Sanchi’ were obtained at 9:08. After the shipwreck was completely scanned, full-precision multibeam images of the ‘Sanchi’ were obtained at 9:08. After the shipwreck was five sampling points were set up in the horizontal and vertical direction of the shipwreck. The sampling completely scanned, five sampling points were set up in the horizontal and vertical direction of the depth was set to 0 m, 0.3 m, 0.5 m, 0.8 m, and 1.0 m and the interval was 10 m. At 10:58, the USV shipwreck. The sampling depth was set to 0 m, 0.3 m, 0.5 m, 0.8 m, and 1.0 m and the interval was 10 m. At 10:58, the USV returned to the mothership and then the technicians immediately extracted the water samples and conducted a comprehensive inspection of the USV. 4.3. Mission Data 4.3.1. Path Following In Figure 15a, the gray straight line indicates the planned path, and the dotted line indicates the actual path of the USV. What we need to explain is that we only focused on the path following error related to the mission, and we did not focus on the path following error during the USV sailing to Appl. Sci. 2020, 10, 2704 15 of 21 returned to the mothership and then the technicians immediately extracted the water samples and conducted a comprehensive inspection of the USV (Supplementary Materials). 4.3. Mission Data 4.3.1. Path Following Appl. Sci. 2020, 10, x FOR PEER REVIEW 15 of 21 In Figure 15a, the gray straight line indicates the planned path, and the dotted line indicates the actual path of the USV. What we need to explain is that we only focused on the path following error the mission area and returning to the mothership. As shown in Figure 15b, the maximum following related to the mission, and we did not focus on the path following error during the USV sailing to the error was 3.2150 m. The following error within 2 m accounts for 97.70%. The data proved that the mission area and returning to the mothership. As shown in Figure 15b, the maximum following error straight path following algorithm can ensure the USV to have high navigation accuracy in this was 3.2150 m. The following error within 2 m accounts for 97.70%. The data proved that the straight mission. path following algorithm can ensure the USV to have high navigation accuracy in this mission. (a) (b) Figure 15. Path following error of the USV: (a) Path of the USV, (b) changes of the path following error Figure 15. Path following error of the USV: (a) Path of the USV, (b) changes of the path following during the mission. error during the mission. 4.3.2. Collision Avoidance 4.3.2. Collision Avoidance Figure 16a–e shows a complete collision avoidance process of our USV during the mission. As shown in Figure 16a, the USV was sailing normally according to the planned path, and a large rescue Figure 16a–e shows a complete collision avoidance process of our USV during the mission. As vessel was coming from the right side of the USV. As shown in Figure 15b–d, when the USV detected shown in Figure 16a, the USV was sailing normally according to the planned path, and a large rescue the vessel, the collision avoidance process started, the USV began to change the path according to the vessel was coming from the right side of the USV. As shown in Figure 15b–d, when the USV collision avoidance parameters, steered to the right, and detoured from the rear side of the vessel until detected the vessel, the collision avoidance process started, the USV began to change the path it successfully and safely bypassed the vessel, and then returned to the planned path. Figure 16e shows according to the collision avoidance parameters, steered to the right, and detoured from the rear side the change of the path during the whole collision avoidance process. of the vessel until it successfully and safely bypassed the vessel, and then returned to the planned Then, we analyzed the changes of the USV’s heading angle and lateral oset during collision path. Figure 16e shows the change of the path during the whole collision avoidance process. avoidance process. As can be seen from Figure 17a,b, during the initial stage, the USV was sailing along the path with an angular direction of 70.219 , while the lateral oset was controlled within 3 m. Starting from 55 s, the USV detected the obstacle and then turned to the right. At this time, the lateral oset started to decrease (the lateral oset was positive on the left side of the path), and, at most, the lateral oset was about 20 m. After completely avoiding the obstacle, the USV began to quickly adjust its path, turn left, and return to the planned path. So the lateral oset gradually increased until it returned to near 0, indicating that the USV returned to the planned path. As shown in Figure 17c, during the whole collision avoidance process, the nearest distance between the USV and the obstacle was 16 m, which is sucient to ensure navigation safety. Figure 16. Process of the collision avoidance: (a) Start collision avoidance, (b,c) collision avoidance, (d) return to the test path after avoiding the obstacle, (e) path in the process of collision avoidance. Then, we analyzed the changes of the USV’s heading angle and lateral offset during collision avoidance process. As can be seen from Figure 17a,b, during the initial stage, the USV was sailing Appl. Sci. 2020, 10, x FOR PEER REVIEW 15 of 21 the mission area and returning to the mothership. As shown in Figure 15b, the maximum following error was 3.2150 m. The following error within 2 m accounts for 97.70%. The data proved that the straight path following algorithm can ensure the USV to have high navigation accuracy in this mission. (a) (b) Figure 15. Path following error of the USV: (a) Path of the USV, (b) changes of the path following error during the mission. 4.3.2. Collision Avoidance Figure 16a–e shows a complete collision avoidance process of our USV during the mission. As shown in Figure 16a, the USV was sailing normally according to the planned path, and a large rescue vessel was coming from the right side of the USV. As shown in Figure 15b–d, when the USV detected the vessel, the collision avoidance process started, the USV began to change the path according to the collision avoidance parameters, steered to the right, and detoured from the rear side of the vessel until it successfully and safely bypassed the vessel, and then returned to the planned Appl. Sci. 2020, 10, 2704 16 of 21 path. Figure 16e shows the change of the path during the whole collision avoidance process. Appl. Sci. 2020, 10, x FOR PEER REVIEW 16 of 21 along the path with an angular direction of 70.219°, while the lateral offset was controlled within 3 m. Starting from 55 s, the USV detected the obstacle and then turned to the right. At this time, the lateral offset started to decrease (the lateral offset was positive on the left side of the path), and, at most, the lateral offset was about −20 m. After completely avoiding the obstacle, the USV began to quickly adjust its path, turn left, and return to the planned path. So the lateral offset gradually increased until it returned to near 0, indicating that the USV returned to the planned path. As shown Figure 16. Process of the collision avoidance: (a) Start collision avoidance, (b,c) collision avoidance, in Figure 17c, during the whole collision avoidance process, the nearest distance between the USV Figure 16. Process of the collision avoidance: (a) Start collision avoidance, (b,c) collision avoidance, (d) return to the test path after avoiding the obstacle, (e) path in the process of collision avoidance. and the obstacle was 16 m, which is sufficient to ensure navigation safety. (d) return to the test path after avoiding the obstacle, (e) path in the process of collision avoidance. Then, we analyzed the changes of the USV’s heading angle and lateral offset during collision avoidance process. As can be seen from Figure 17a,b, during the initial stage, the USV was sailing (a) (b) (c) Figure 17. Collision avoidance results of the USV. (a) Changes in heading angle. (b) Changes in Figure 17. Collision avoidance results of the USV. (a) Changes in heading angle. (b) Changes in lateral lateral offset. (c) Change in distance between the USV and the obstacle center. oset. (c) Change in distance between the USV and the obstacle center. 4.3.3. Scan 4.3.3. Scan Figure 18a represents the front view of the shipwreck, where you can see the total length of Figure 18a represents the front view of the shipwreck, where you can see the total length of the the shipwreck was 274 m. Figure 18b shows the side view of the shipwreck. We can see that the shipwreck was 274 m. Figure 18b shows the side view of the shipwreck. We can see that the prominent cockpit was perpendicular to the surface of the seabed, indicating that the shipwreck was prominent cockpit was perpendicular to the surface of the seabed, indicating that the shipwreck was also perpendicular to the surface of the seabed. also perpendicular to the surface of the seabed. Appl. Sci. 2020, 10, 2704 17 of 21 Appl. Sci. 2020, 10, x FOR PEER REVIEW 17 of 21 (a) (b) Figure 18. ‘Sanchi’ multibeam view: (a) Shipwreck front view, (b) shipwreck side view. Figure 18. ‘Sanchi’ multibeam view: (a) Shipwreck front view, (b) shipwreck side view. By preliminary judgment, the oil spill point was located in the position where the hull was hit in By preliminary judgment, the oil spill point was located in the position where the hull was hit in the accident. It is well known that a huge impact can cause a partial structural loss of the hull, so the the accident. It is well known that a huge impact can cause a partial structural loss of the hull, so the location where the structural loss occurs is the point of the impact. Referring to Figure 19a, we found a location where the structural loss occurs is the point of the impact. Referring to Figure 19a, we found gap in the front view. In order to further judge whether the gap was caused by the collision, we took a gap in the front view. In order to further judge whether the gap was caused by the collision, we the cross-section 1 at the gap and took another cross-section 2 near the 1, then generated the height took the cross-section 1 at the gap and took another cross-section 2 near the 1, then generated the change diagram of the two cross-sections. Referring to the Figure 19b,c, we found that the cross-section height change diagram of the two cross-sections. Referring to the Figure 19b,c, we found that the 1 had a significant drop in height at the same location compared with the cross-section 2, indicating cross-section 1 had a significant drop in height at the same location compared with the cross-section that the cross-section 1 had a structural loss. Combined with the dimensional structure data of the 2, indicating that the cross-section 1 had a structural loss. Combined with the dimensional structure ‘Sanchi’ oil tanker, we confirmed that the gap in Figure 19a was caused by the collision, and the oil spill data of the ‘Sanchi’ oil tanker, we confirmed that the gap in Figure 19a was caused by the collision, point was at this gap. and the oil spill point was at this gap. The multibeam images not only helped us confirm the position and posture of the shipwreck, The multibeam images not only helped us confirm the position and posture of the shipwreck, but also found the position of the impact to confirm the point of the oil spill. On the one hand, this but also found the position of the impact to confirm the point of the oil spill. On the one hand, this information helped us infer the oil spill rate of the shipwreck and adjust the mission plan in time. information helped us infer the oil spill rate of the shipwreck and adjust the mission plan in time. On On the other hand, it provided strong evidence for future accident investigation. the other hand, it provided strong evidence for future accident investigation. Appl. Sci. 2020, 10, 2704 18 of 21 Appl. Sci. 2020, 10, x FOR PEER REVIEW 18 of 21 (a) (b) (c) Figure Figure19. 19.Cr Coss-sectional ross-sectional view view of o‘Sanchi’ f ‘Sanchi multibeam: ’ multibeam (:a ) (a Cr ) C oss-section ross-sectioposition, n positio( n b , )(height b) heigchange ht chanof ge cr ooss-sections f cross-sectio1, ns( c 1), height (c) heig change ht chanof gecr ooss-sections f cross-sectio 2. ns 2. 4.3.4. Water Sampling 4.3.4. Water Sampling Our USV collected a total of 5 bottles of the water samples (2000 mL per bottle) at 5 dierent Our USV collected a total of 5 bottles of the water samples (2000 mL per bottle) at 5 different locations. After the USV returned to the mothership, the China State Oceanic Administration analyzed locations. After the USV returned to the mothership, the China State Oceanic Administration the water samples. Figure 20 shows the collected water samples. Since oil can change and destroy analyzed the water samples. Figure 20 shows the collected water samples. Since oil can change and the normal ecological balance in the water, serious oil spill accidents often destroy the ecological destroy the normal ecological balance in the water, serious oil spill accidents often destroy the environment for decades. Therefore, water quality monitoring must be carried out through the mission ecological environment for decades. Therefore, water quality monitoring must be carried out and operate for a long time after this mission. Even if the oil concentration in the water basically through the mission and operate for a long time after this mission. Even if the oil concentration in the returns to normal, monitoring cannot be stopped until the ecological environment is fully restored. water basically returns to normal, monitoring cannot be stopped until the ecological environment is fully restored. Appl. Sci. 2020, 10, 2704 19 of 21 Appl. Sci. 2020, 10, x FOR PEER REVIEW 19 of 21 Figure 20. The water samples. Figure 20. The water samples. 5. Conclusions 5. Conclusion This paper described the application of our USV in the emergency response mission for the This paper described the application of our USV in the emergency response mission for the ‘Sanchi’ oil tanker collision and explosion accident. The improved algorithms of navigation control, ‘Sanchi’ oil tanker collision and explosion accident. The improved algorithms of navigation control, an improved automatic LARS, and a new special sampling system allowed the USV to be quickly an improved automatic LARS, and a new special sampling system allowed the USV to be quickly deployed to the mission area, and enabled the USV to have higher navigation accuracy and navigation deployed to the mission area, and enabled the USV to have higher navigation accuracy and safety in the mission. In this mission, the USV performed the real-time scanning and sampling, which navigation safety in the mission. In this mission, the USV performed the real-time scanning and provided important information for determining the exact location of the shipwreck, locating the oil sampling, which provided important information for determining the exact location of the spill point, estimating the amount of oil spilled, salvaging the shipwreck, and evaluating the pollution. shipwreck, locating the oil spill point, estimating the amount of oil spilled, salvaging the shipwreck, The information not only provided a lot of help to rescuers, but also oered a scientific basis for the and evaluating the pollution. The information not only provided a lot of help to rescuers, but also follow-up work (such as ecological recovery, accident identification, etc.). offered a scientific basis for the follow-up work (such as ecological recovery, accident identification, Although the USV completed the mission, we also found some new issues in the mission, such as etc.). the stability of the USV was insucient. Especially in poor sea states, the negative impact of the Although the USV completed the mission, we also found some new issues in the mission, such environmental disturbances (winds, waves, and currents, etc.) on the stability was particularly evident. as the stability of the USV was insufficient. Especially in poor sea states, the negative impact of the The capability of a single USV was also limited. Due to the limitations of the speed and the payload, a environmental disturbances (winds, waves, and currents, etc.) on the stability was particularly single USV had to take a long time to complete a complex mission. Once the USV breaks down in the evident. The capability of a single USV was also limited. Due to the limitations of the speed and the process of working, the mission must be suspended. payload, a single USV had to take a long time to complete a complex mission. Once the USV breaks We will continue to solve the above issues by actively predicting the environmental disturbances’ down in the process of working, the mission must be suspended. information and establishing a multiple USVs’ system. Active prediction of the environmental We will continue to solve the above issues by actively predicting the environmental disturbance information for the USVs can calculate the compensation instructions in advance according disturbances’ information and establishing a multiple USVs’ system. Active prediction of the to environmental disturbances, so that the stability of USVs can be improved. Multiple USVs’ system environmental disturbance information for the USVs can calculate the compensation instructions in with the cooperation between the USVs can enhance the USVs’ robustness and reliability, improve advance according to environmental disturbances, so that the stability of USVs can be improved. mission performance, reduce costs, and provide the best mission policy. Multiple USVs’ system with the cooperation between the USVs can enhance the USVs’ robustness Supplementary and reliabilityMaterials: , improve The miss following ion perfo ar rm e available ance, red online uce co at sthttp: s, an// d www prov .mdpi.com ide the be /2076- st mi3417 ssio/n 10 p /8 o/l2704 icy. /s1, Video: Collision avoidance, Deployment, Recovery. Author Contributions: Author Contributions: H.P., Y.L., J.L., S.X., Y.P. designed USVs; Y.Y. (Yang Yang), X.L., C.Z., J.K., J.C. and D.Q. carried out the missions; Y.L., Z.S., W.S. analyzed mission results. H.P., Y.Y. (Yi Yang), S.G. analyzed sequencing Huayan Pu, Yuan Liu, Jun Luo, Shaorong Xie, Yan Peng * designed USVs; Yang Yang, Xiaomao Li, Chuang data and developed analysis tools. Y.L. wrote the manuscript. All authors have read and agreed to the published Zhu, Jun Ke, Jianxiang Cui and Dong Qu carried out the missions; Yuan Liu, Zhou Su, Wenyun Shao analyzed version of the manuscript. mission results. Huayan Pu, Yi Yang, Shouwei Gao analyzed sequencing data and developed analysis tools. Funding: This work was supported in part by the National Natural Science Foundation of China (9174810194). Yuan Liu wrote the manuscript. Acknowledgments: The authors wish to thank the State Oceanic Administration of China, the Maritime Search Funding: This work was supported in part by the National Natural Science Foundation of China (9174810194). and Rescue Center of China, and the Maritime Search and Rescue Center of Shanghai that have helped in the missions. Acknowledgments: Conflicts of Interest: The authors declare there is no conflicts of interest regarding the publication of this paper. The authors wish to thank the State Oceanic Administration of China, the Maritime Search and Rescue Center of China, and the Maritime Search and Rescue Center of Shanghai that have helped in the missions. Appl. Sci. 2020, 10, 2704 20 of 21 Abbreviations Unmanned Surface Vehicle USV launch and recovery system LARS Autonomous Underwater Vehicle AUV Remote Operated Vehicle ROV Knot kn Global Positioning System GPS Inertial Navigation System INS Light Detection and Ranging LiDAR References 1. Tiron, R. High-Speed Unmanned Craft Eyed for Surveillance Role. Natl. Def. 2002, 5, 27. 2. Accurate Automation Corporation. Available online: https://www.accurateautomation.com/content/Home (accessed on 1 December 2019). 3. C-Target3. Available online: https://www.asvglobal.com/product/c-target-3/ (accessed on 5 December 2019). 4. 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