TOWARD COOPERATIVE UNDERWATER ROBOTS FOR ECOLOGICAL SURVEILLANCE OF MARINE AND UNDERWATER ENVIRONMENTS J. Batlle, P. Ridao, M. Carreras and V. Ila Institute of Informatics and Applications. University of Girona Avda. Lluis Santaló s/n. 17003-GIRONA, SPAIN tel: 34 972 418767 fax: 34 972 418098 email: (jbatlle,pere,marcc,
[email protected])
Abstract The objective of this paper is to present a downsized prototype of an Autonomous Underwater Vehicle (AUV) designed with the idea of dealing with cooperative tasks involving multiple agents. The entire system has been designed for marine and underwater environmental surveillance and protection. The agents provide an interesting point in the surveillance of shallow coastal waters and shallow waters up to 100m in depth, where the pollution effect is most important. In addition, the vehicles are useful in a similar way in fresh-water environments such as lakes and reservoirs. The main topics involved are underwater communications, underwater imaging, agents and cooperative agents.
1. Introduction Ecological surveillance of underwater environments is an important challenge in controlling water contamination. The greater part of the world’s pollution is found in coastal waters up to 100 meters. Supervision of these zones is done by collecting samples of water and sediments. These collecting measures are very important in order to analyse the degree of pollution and to predict potential disasters such as a reduction of plankton or an uncontrolled overgrowth of tropical seaweed. These measures are currently taken by scuba divers who can dive up to only 40 meters for periods of not more than 40 minutes. On many occasions, divers have to work in very dangerous environments such as dams and lakes and, in some specific areas, sensors attached to ropes carried by ships or fixed to anchors or buoys are also used to reduce risk and insure accuracy.This paper proposes a cooperative system of agents based on underwater robots for marine and underwater environmental protection. This multi-agent system has been designed to eliminate dangerous work for scuba divers and to expand the boundaries of depth and time of missions. These robots will be able to navigate autonomously, locate the interesting areas
and collect water and sediment samples from small materials such as stones and seaweed by using an electrically controlled articulated claw. As a result of the cooperative behaviour of the agents, it is expected that the system will be able to cover large extensions of the coastal area in each mission. Also, the vehicles have been designed as low cost, small sized submarines, which means that the use of a big fleet of agents will be affordable and the mobility of the whole system facilitated. This paper concentrates on the description of the underwater vehicle which will carry out the cooperative surveillance tasks. The prototype, called URIS (Underwater Robot for Intelligent Software), has been developed in the Institute of Informatics and Applications of the University of Girona. The design is based on the experience acquired over the years with the underwater vehicle GARBI. Emphasis has been placed on in the reduction of size in order to increase the portability of the vehicle and autonomy, in both the control and the power levels, has been searched. The structure of this paper is as follows. Section 2 describes the ecological surveillance tasks in which the proposed multi-agents systems will be used. Then, a brief description of the previously developed vehicle GARBI is done in the section 3. In section 4, the new downsized, low-cost prototype URIS is described. Finally, conclusions and future work are presented in section 5.
2 The ecological surveillance task From an ecological point of view, the control of pollution and its effect on seaweed and plankton is very important in order to predict fish and seafood evolution and to formulate non prejudicial fishing practices. In addition, water quality is one of the most important factors in deciding whether a beach is safe or in need of attention. Local water temperature is helpful in predicting the proliferation of jellyfish and gives time to warn swimmers to stay in safe bathing areas. Also, it is very advantageous to detect sea flows and their movements in order to predict the most highly polluted areas and advise swimmers on the degree of pollution. To these ends, this ecological surveillance system has been designed to collect temperature values and samples at several points. This system is able to cover coastal waters up to a depth of 100m depths where the pollution effect is most important. A set of different end-effectors will be built in order to allow the collection of diverse samples such as water, sediment or seaweed using electrically controlled claws and bins. The robots will be programmed with a set of tasks so that they will navigate from the dock or host ship, accomplish the tasks and return to the starting point. Then, without any risk, scientists can easily remove the samples for analization. The use of low-cost AUVs will increase the number of measuring areas and will allow the scientist to change those areas dynamically, allowing a descent of up to 100 meters with a mission time of up to 1 hour. Figure 1 shows several underwater robots carrying out a task.Communication with other robots and with a central station is done using acoustic links. Cooperation [mack1] between the robots is used to arrive at the best distribution for collecting the samples by each agent. Each vehicle is in charge of collecting the samples of a particular zone.
However, if a vehicle has any problem, their samples will be collected by one of the other robots. This will insure the complete execution of the mission. Surface AUV
AUV
AUV AUV
AUV
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Figure 1. AUV’s carrying out a task. The determination of position, course and velocity at any moment is necessary for navigation. The techniques may be divided in two main categories [geye2]: relative and absolute navigation. Relative navigation refers to the integration of velocity or acceleration (Inertial Navigation Systems, speed sensors, etc), into the systems. However, position error of this estimate increases in time. Absolute positioning is achieved by computing the relative measurements to a reference (acoustic beacons, compass, etc). The agents use a self-locating system with absolute and relative positioning. Under water, relative navigation will estimate the position. To find the absolute position the submarine will emerge and use a DGPS (accuracy 1-5 m.).
3 The precedent, GARBI robot The GARBI [amat3] robot was built at the University of Girona in conjunction with the Politechnical University of Catalunya. This vehicle was first conceived as a Remotely Operated Vehicle (ROV), for exploration in waters up to 200 meters in depth. At the moment a control architecture is being implemented to transform this vehicle into an Autonomous Underwater Vehicle (AUV). GARBI, see figure 2, was designed with the aim of building an underwater vehicle using low cost materials, such as fibber-glass and epoxy resins. To solve the problem of resistance to underwater pressure, the vehicle was servo-pressurised to the external pressure by using a compressed air bottle, like those used in scuba diving. Air consumption is required only in the vertical displacements during which the decompression valves release the required amount of air to maintain the internal pressure at the same level as the external one. Also, this vehicle is able to incorporate two arms, which would allow it to perform some tasks of object manipulation through tele-operation. GARBI possesses four thrusters; two for horizontal movements (axis x) and two for vertical movements (axis z). Additionally, it is possible to add another thruster in the transverse direction (axis y). Due to the distribution of weight, the vehicle is completely stable. Pitch and roll angles are continually insignificant. For this reason the vertical and horizontal movements are totally independent. This vehicle also has several sensors: 2 compasses, 2
pressure sensors, 2 water speed sensors and 5 sonar sensors. Dimensions are: length 1.3 m., height 0.9 m and width 0.7 m. Maximum speed is 3 knots and the weight is 150 Kg.
Figure 2. GARBI underwater vehicle.
4. The prototype URIS The underwater robot URIS has been designed based on the knowledge and experience acquired with GARBI. The most important improvements have been downsizing and giving complete autonomy in control and power. These characteristics together with the low cost of the vehicle make the use of a large fleet of submarines for ecological surveillance both manageable and economically feasible. The vehicle is powered by a package of batteries giving autonomy of more than an hour. Table 1 summarises the main characteristics of this cooperative vehicle and figure 3 shows a photograph of the actual vehicle. Kind D.O.F. Stability Propulsion Energy Max. depth Sensors
Autonomous Underwater Vehicle (AUV) 4 (x,y,z,Yaw) Passively stable in Roll and Pitch 4 thrusters (20W x 15V DC motor + dynamo) 4 packages of NiCd batteries (50 W x 12V) 100 meters Magnetic compass (Yaw) Pressure sensor (z) Obstacle detection system using sonar sensors Acoustic communication Vision system (RGB+laser) Speed sensor DGPS Water and battery charge detection Table 1. Characteristics of URIS.
Figure 3. The URIS underwater vehicle.
4.1 The structure The hull has been designed as a sphere, see figure 3, as a result, offers the same hydrodynamic damping in any direction. There have been precedents with this shape like the ODIN [choi4] submarine of the University of Hawaii-USA or the ROBIN robot of CNRIAN-Italy. This structure simplifies the construction of a dynamic model of the vehicle, which is very useful for simulation of missions in the laboratory.The hull consists of two stainless steel hemispheres joined with wing nuts and bolts, see figure 4. The structure has been designed to withstand pressures of 10 atmospheres, the equivalent of a depth of 100 meters. The interior has been designed with the idea of grouping the different devices in independent modules. This distribution allows easy separation of the two hemispheres for working on each module in the laboratory. This distribution also takes into account the weight of the modules. Hence, the heavier devices (batteries, power cards and propellers) have been placed in the bottom of the robot placing the centre of gravity lower than the buoyancy centre. This configuration insures the stability of the vehicle in roll and pitch, and therefore, don’t have to be controlled.
Figure 4. The hull and battery packages.
Figure 5.Photograph of a thruster.
4.2 The power The power system of the robot consists of 4 packages of batteries which provide 216 W·h, see figure 4. The maximum consumption of the various devices allows an autonomy of more than an hour. This time has been calculated to be long enough to fulfil the mission requirements. On the other hand, the vehicle can also be powered by an external source using an umbilical cable. This option facilitates the tune-up of the controllers in the developmental phase when a lot of experiments are required.
4.3 Propulsion The propulsion of the vehicle is achieved with 4 thrusters placed equidistant on the vehicle’s exterior, see figure 5. Due to the stability of the vehicle in pitch and roll, there are four degrees of freedom; X, Y, Z and Yaw. The propulsion system controls the degrees of freedom X, Y and Yaw. The horizontal thrusters (X1 and X2) are used for movements in X and Yaw, see figure 6. The X movement is determined by the sum of the two propellers, and the Yaw movement by subtraction. Vertical movement is controlled with two thrusters (Z1 and Z2). The degree of freedom Y isn’t directly controlled. Each thruster is composed of a c.c. motor, a helix and a dynamo. To increase efficiency, a duct has been placed around the helix. (Motor characteristics: DC MAXON, P= 20W, V= 15 V, speed= 10000rpm, red.: 5.8:1, dynamo:[0 10]V).
4.4 The sensors In order to perceive interaction with the environment, the robot has several sensors: • Magnetic compass (Yaw). An electronic compass is used to detect the absolute Yaw value of the vehicle. (Characteristics: Precisión Navigation Inc, Vector 2XG, Precision: ±2º, resolution: 1º, frequency: 0.4 Hz) • Pressure sensor (z). This provides water pressure information and consequently the depth of the vehicle. (Characteristics: Keller AG, mod. PA-21R-10, Range: 0-10 bar, Vcc= 8-28V, Iout= 4-20 mA.) • Obstacle detection system. Any obstacles in the vicinity of the robot are detected by means of 7 sonar transducers. The sensors are distributed in the horizontal and vertical planes with 6 and 1 units respectively. (Characteristics: Moher Suministros electrónicos, Range: [0 40]m , detection degree: 20º, Vcc:12V, I=55 mA, Output: [0 10]V). • Acoustic communication system. It uses an Airmar transducer working on two frequencies to encode binary data.
Figure 6. Propulsion system of URIS. An electrical board is used to send and receive information from the transducer. Recent results have shown the feasibility of the system. This system is still in the process of being developed [cruz5]. •
Vision system (RGB+laser). Two different applications are currently being developed.
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The first is an automatic video mosaic of the ocean floor [garc6]. A mosaic is a composite image constructed by combining a set of smaller images. Mosaics are very useful in undersea exploration, the creation of visual maps, navigation, and so forth. The method used to combine the image is based on textural parameters of certain parts of the image. This application uses a camera and a sonar sensor to detect the distance of the scene. The second application is a fully operative 3D vision measurement system [fore7]. It uses a slit laser beam with a camera. A method for automatically calibrating the laser with few restrictions of position and orientation is used. Once the system is calibrated, we can sweep a scene by moving the laser beam obtaining the 3D points of the illuminated objects, and therefore, the 3D environment. • Speed sensor. A flux-meter sensor is used to compute the horizontal speed of the vehicle and estimate the position. • DGPS. This is used to obtain the absolute position when the vehicle is not submerged. The precision is between 1 and 5 meters. • Water and battery charge detection. There are two internal safety sensors to prevent the integrity of the vehicle from being broached. The water sensor detects any water seepage at several points of the vehicle and in each propeller. Another sensor supervises the charging of the 4 packages of batteries in order to avoid unexpected loss of power.
4.5 Hardware architecture The computing system is compounded of: • An external PC. This is used for development and debugging of the software executed onboard. It is also used to execute the interface with a human operator. It allows the operator to send control commands for executing the mission to the robot. During the
development of the software it allows the monitoring of the robot’s performance. This PC can be linked to the onboard PC with a 10 Mbs ethernet connection. • Onboard System. This consists of a Pentium PC equipped with peripheral units. This system gathers other boards which manage all the devices (sensors, batteries,...) and also optimises the functioning of the PC. The link between the boards and the PC is done through a serial connection. Because of the small size of the robot, a computational system based on the industrial PC of type 104 has been chosen. These PC have electronic boards of 92mm x 96mm in dimension which can be placed horizontally one over the other.
4.6 Software systems An environment called DEVRE (Distributed Environment for Virtual and/or Real Experimentation) has been developped to control, design and implement missions. DEVRE is an integrated software platform composed of three modules: •
Human Machine Interface (HMI). This is an interface with a human operator, executed on the external PC. It allows vehicle monitoring as well as sending commands, see figure 7. Its main functions are the following:
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Monitoring the state of the sensors during the mission: their values are shown on a control panel. Logging sensor readings: sensor data is saved in a file for post-mission study purposes. Sending commands to the control architecture (such as enabling or disabling robot behaviours). Sensor calibration (such as definitions of zero depth pressure). - Low level teleoperation of the vehicle (using a joystick to send commands to the low level controller). - Switching between real and virtual environments. HMI uses a custom defined protocol to provide message frames for each of its functions. It also provides frames for communication between OOCAA and MMVVE. HMI is used in the tune-up phase. • Mathematical Model of the Vehicle and the Virtual Environment (MMVVE). This program has two functions: (1) simulation of the movement of the vehicle underwater using a dynamic model [foss8] and (2) providing a virtual representation of the underwater world, see figure 8. The usefulness of the world model is twofold. First, it allows the visualisation of the vehicle within the environment and second, the simulation of the sensors providing environmentally dependent information like sonar. The MMVVE is used in the overall design of the mission. •
Object Oriented Control Architecture (OOCAA). This program is the high level control of the robot. It is a hybrid deliberative-reactive control architecture [rida9] in
Figure 7. HMI graphical interface.
Figure 8. MMVVE interface.
charge of controlling the vehicle during a mission. The control software is arranged in three layers: The Deliberative Layer is used for mission planning. It is in charge of inserting new tasks in the plan structure in an effort to minimise the cost function. The Control Execution layer is responsible for the plan representation and controlling its execution. The plan is represented as a finite state machine in which each state is related to one task. The execution of the related task means turning on or off a set of behaviours for each state. The real time control of the vehicle is in charge of the reactive layer which provides the three reactive mechanisms: (1) behaviours, (2) monitors and (3) timers. The behaviours are real input values from the sensor subsystem and use fuzzy If-THEN rules to compute the new set points for the low level controller. Monitors are used for situation recognition and event handling. Timers are used for computing deadlines. All these programmes are written in different languages and run on different computers under different operating systems. HMI and MMVVE modules are programmed in LabWindows and executed on two different PCs under Win32 OS. The OOCAA is programmed in C++ and executed on the onboard pentium computer running VxWorks. All components are networked through a TCP/IP LAN (10 Mbs Ethernet). When the robot is moving autonomously in the water, the HML interface is used to set the mission and then the OOCAA is executed on the onboard computer without any connection with the surface. During the development of the software, we can keep HMI and OOCAA networked through a TCP/IP and watch the development of the mission on the PC at the surface. Because of the complexity of the development of the software for the autonomous underwater robot and because of the fact that it is done in parallel with the construction of the vehicle, it is necessary to use a virtual simulator of the vehicle and the environment (MMVVE). HMI and OOCAA can be dynamically configured to act on the virtual simulator instead of the real robot. The goal of the simulator is not to eliminate the real tests, but to be used in the experiments performed in the laboratory during the development of the software.
5. Conclusions and future work A proposal for ecological surveillance of shallow and relatively shallow water environments has been described. The system involves a colony of underwater agents, which, by means of cooperation, will acquire temperature, water samples and sediments at several points. This proposed system will be useful in extending the number and boundary limits of measurement points which are currently being collected by scuba divers. This paper has presented a downsized prototype of an Autonomous Underwater Vehicle (AUV), called URIS, conceived as low-cost small submarine. A complete description of the vehicle has been made. This vehicle has already been tested proving it has excellent manoeuvrability. At the time of writing, the execution of a mission using only one vehicle is being tested. For future work, different systems will have to be developed until a viable ecological surveillance system is achieved. Cooperation techniques, a self-positioning system and a sampler device are different aspects being developed at this time. Finally, the replication of the robot URIS will carry us to the cooperative multi-agent system for ecological surveillance.
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