SAUC-E 2010 Journal Paper ENSIETA

Transcription

1 SAUC-E 2010 Journal Paper ENSIETA Fabrice LE BARS, Jan SLIWKA, Luc JAULIN et al.

2 SAUC-E 2010 Journal Paper ENSIETA 2 CONTENT I. EXECUTIVE SUMMARY... 3 II. INTRODUCTION... 4 III. PHYSICAL DESCRIPTION... 5 External architecture:... 5 Internal architecture:... 7 Electronic architecture:... 8 IV. AUTONOMY AND MISSION PLANNING V. INNOVATION VI. FINANCIAL SUMMARY VII. RISK ASSESSMENT VIII. REFERENCES

3 SAUC-E 2010 Journal Paper ENSIETA 3 I. Executive summary As last year and since 2007, the ENSIETA (Ecole Nationale Supérieure des Ingénieurs des Etudes et Techniques d'armement) will take part to the SAUC-E competition. This year, we mainly focused on thinking about solutions that could improve the reliability and the flexibility of every parts of the submarine. Additionally, we tried to introduce the idea of a collaborating swarm of submarines by building a new robot. 3

4 SAUC-E 2010 Journal Paper ENSIETA 4 II. Introduction The SAUC ISSE submarine robot has proven across the years that several choices we made were efficient. As a consequence, after many discussions we decided to keep the same basis (tube with 3 thrusters ) for the existing submarine (SAUC ISSE) and the new one (called camera-robot). The main aim of the camera-robot will be to follow SAUC ISSE autonomously to take underwater videos of it. It should be also able to do some camera related tasks of the competition. We decided to build an additional submarine for several reasons: It would be a good way to test new ideas without loosing in reliability (as we could keep the existing one with the old but reliable concepts). It would be the beginning of a collaborating swarm of robots in a submarine context, which would introduce something new. For example, instead of using a single complicated robot with several different sensors, we could use several different and more simple robots with each one designed for a dedicated task (a camera-robot, a sonarrobot, ). As most of the work is done by several students, having several robots helps them to test and practice more. It could replace the old one in case of a problem. We also made some minor changes on SAUC ISSE: reorganisation of the different internal and external connectors to improve the flexibility, new cameras First, we will detail the physical architecture (mechanical and electronic) of our robots. Then, we will explain how we will handle the autonomy of each robot and the missions. A part pointing out the innovations made this year will follow. Finally, a financial summary and a risk assessment table will be provided. 4

5 SAUC-E 2010 Journal Paper ENSIETA 5 III. Physical Description External architecture: The existing and the new robots share the same mechanical base (Figure 1). Indeed, an aluminum tube is a good choice for its resistance to pressure, its amagnetism, its resistance to corrosion, and its facility to prepare a watertight environment. Its size is no more than 70 cm long to ease its transportation and reduce its weight, as the space inside is sufficient to contain all the needed devices. The diameter of the tube for the new submarine has been chosen to 20 cm to be able to put an EeePC as embedded computer (contrary to a PC/104 in SAUC ISSE). Figure 1 : SAUC ISSE in water and the new camera-robot in simulation The watertightness of each tube is made by two aluminum plaques (Figure 2). There are waterproof connectors (Switchcraft and Bulgin Buccaneer) on the plaques for the various sensors and actuators of the robot. The watertightness is provided by three stainless fastener screws. The fixation of the screws is done with a pawn center. The extraction of plaques is done with three extraction screws. The front plaque of the camera-robot has a window to enable the use of a webcam directly in the tube. All the waterproof connectors are on the rear plaque. This plaque should only be opened in case of a problem, as opening the front plaque will enable to change the batteries and switch on the EeePC. Therefore, only the front plaque should be opened for normal operation. The principle is the same for SAUC ISSE. Figure 2: The rear plaque of SAUC ISSE with its waterproof connectors (interior side) and the front plaque of the camera robot with a window A special structure (Figure 3) was made to carry the horizontal thrusters. 5

6 SAUC-E 2010 Journal Paper ENSIETA 6 Figure 3: Structure that carries the horizontal thrusters of SAUC ISSE The roll and pitch are not controlled but are stable thanks to a weighted keel, what is also a support for the sonar and the vertical thruster (Figure 4). The keel is cut to put our vertical thruster in the center of the submarine, in order to keep symmetry. Figure 4: Vertical thruster centered in the keel Additionally, we have a system to adjust the overall ballast of the submarine: breakthrough mass lead can be added on 4 threaded rods placed in the four corners of the submarine so we can reach the limit zone of buoyancy. As a result we just need a propelling force very weak to make the submarine go under the surface, and when the vertical engine is shut down, it goes itself to the surface. 6

7 SAUC-E 2010 Journal Paper ENSIETA 7 Internal architecture: Rails (Figure 5) with glue for aluminum enable us to drag a Plexiglas plaque of 6mm width which is the main support base for the internal electronic devices of SAUC ISSE. Figure 5: Rails inside the tube of SAUC ISSE Below the plaque, another sliding support (Figure 6) contains the batteries. Thus, we can readily access the batteries without having to touch any of the other electronic devices. These are put above the main Plexiglas plaque. Figure 6: Sliding support and internal devices in SAUC ISSE The internal architecture of the camera-robot is almost the same (Figure 7). Figure 7: Internal devices of the camera robot 7

8 SAUC-E 2010 Journal Paper ENSIETA 8 Electronic architecture: Thrusters (3) Electrical cables Thrusters controllers (3) PWM Labjack UE9 Electrical cables PWM PWM Electrical cables Sonar USB Embedded computer IMU (compass) USB Pressure sensor USB Ethernet Figure 8: Electronic architecture We use 3 thrusters STB150 from SEABOTIX (Figure 9), an American manufacturer specialized in ROVs (Remote Operated Vehicles) to make the robot move: 1 vertical thruster to adjust the depth of the submarine. 2 horizontal thrusters to control the speed and the direction. They are delivered assembled and are made by professionals. Until now, they seem to be reliable because we never had any problem with them (especially watertightness problems like we had with the previous thrusters we used in 2007). Figure 9: SEABOTIX thruster To control the thrusters with electronic signals, we use a servo controller Robbe Rokraft (Figure 10). 8

9 SAUC-E 2010 Journal Paper ENSIETA 9 Battery with Tamiya connector PWM signals, servomotor connector Thrusters Figure 10: Thruster controller The power sent to the thrusters (and therefore their speed) depends on the PWM (Pulse Width Modulation) signal. U : tension of the PWM (5 V) t : pulse width (between 1 and 2 ms) T : period (20 ms) Motor state Motor stopped Turn in a direction Turn in the other direction Pulse width 1.5 ms 1.5 to 2.0 ms 1.0 to 1.5 ms Stopped Figure 11: PWM signals To generate these PWM signals from computer programs, we need an interface module between the computer and the servo controllers: the Labjack UE9 (Figure 12). It is a professional USB device that provides several IO pins to connect to electronic devices. 9

10 SAUC-E 2010 Journal Paper ENSIETA 10 Figure 12: Labjack UE9 generating PWM signals The embedded computer of SAUC ISSE is a PC/104 from EUROTECH with a Pentium M 1.4 GHz CPU and 512 MB of RAM (Figure 13). The operating system and the programs are stored on a hard drive 2.5 of 320 GB. 8 USB, 1 Ethernet, 2 RS232 and 1 VGA ports provide all we need to connect external devices and communicate with the computer. Figure 13: PC/104 CPU module It is powered directly from 12 or 24 V batteries thanks to a power supply module compliant with the PC/104 standard that provides regulated 3.3, 5, +12 and -12 V (Figure 14). Figure 14: Power supply module for the PC/104 The embedded computer of the camera-robot is an ASUS EeePC T91MT (Figure 15). We chose it as a test as it is cheaper than the PC/104, a little bit shorter (slim) and has an integrated battery allowing an autonomy of up to 6 hours, with almost the same technical characteristics (CPU, RAM ). It just needs a USB hub to connect to all needed devices. Figure 15: ASUS EeePC T91MT used in the camera-robot 10

11 SAUC-E 2010 Journal Paper ENSIETA 11 To detect the objects in the basin (especially the mid-water target and the pipeline) and enable the camera-robot to follow autonomously SAUC ISSE, we have standard webcams Logitech Quickcam Pro 9000, which can get pictures with a very high resolution (1600x1200). Moreover, the common defaults in webcam pictures such as distortions and light or color problems are automatically handled by its integrated filter. Their integrated microphone could also be used to communicate with the robot, for example by telling it to start, stop... One of the webcam is put directly in the tube of the camera-robot behind the front plaque window. Other webcams were made waterproof by putting them in house water systems tubes with a Plexiglas window (Figure 16: Webcams). Figure 16: Webcams For SAUC ISSE, we bought analog waterproof webcams ALLWAN AL-2121 that are connected to the embedded computer via an audio-video to USB converter (Figure 17). Figure 17: Analog waterproof cameras and audio-video to USB converter from Grabbino To get the depth of the submarines, we use a professional pressure sensor Keller PAA33X connected to the computer with a RS485 to USB converter (Figure 18). The sensor is fixed on the rear plaque of the submarines. Figure 18: Pressure sensor An IMU (Inertial Measurement Unit) Xsens MTi (Figure 19) lent by the GESMA (Groupe d Etudes Sous Marines de l Atlantique) is used to get the orientation of SAUC ISSE in the basin. It has a built-in fusion filter that uses magnetic data and gyroscopes to get a correct orientation even in case of magnetic disturbances. It is connected to the embedded computer via a RS232 to USB converter. We bought an MTi-G (the same, but with a GPS) for the camera-robot. The GPS function is not used. 11

12 SAUC-E 2010 Journal Paper ENSIETA 12 Figure 19: IMU The main sensor to get the position of the robot in the basin is the MiniKing imaging sonar from Tritech (Figure 20), lent by other people in our school. It is also connected to the embedded computer via a RS232 to USB converter. It should only be mounted on SAUC ISSE. Figure 20: Sonar A wireless access point DWL G700AP (Figure 21) in combination with an external antenna of 1 m enables the robot to communicate with us (via a laptop) when it is near the water surface. If the robot needs to be controlled at higher depths, the antenna is put on a buoy connected to the submarine with a wire of up to 5 m (using SMB Bulgin Buccaneer waterproof connectors with a RG174 cable). Figure 21: Wireless access point The power supply of SAUC ISSE is divided into 2 parts (Figure 22): The engines are powered by a 12 V battery The PC/104, the wireless access point (via the 5 V provided by the power supply PC/104 module) and the sonar are powered by a 24 V battery. Figure 22 : Ni-MH batteries All the other devices (pressure sensor, IMU, Labjack, webcams ) are powered via the USB ports of the computer. 12

13 SAUC-E 2010 Journal Paper ENSIETA 13 The camera robot has only one 12 V battery to power its thrusters, all the other devices are powered by the integrated battery of the EeePC, via the 5 V of its USB ports. 13

14 SAUC-E 2010 Journal Paper ENSIETA 14 IV. Autonomy and mission planning We have several methods to do the competition tasks: some are interesting because they are simple to find or implement, some are a good compromise between simplicity, reliability and accuracy, some are useful in case a sensor is not available for any reason (hardware failure, perturbations...), other are challenging and could have an academic interest. From the point of view of the control part of the submarine, we can consider all the competition tasks as a succession and combination between a depth, orientation and distance regulations problems that change over the time. Depending on the task, these regulations will be used with respect to a coordinate space (waypoints) or to an object (mid-water target detection ). As the roll and the pitch of the submarine should always remain stable by design, the localization problem of the submarine in the basin can be considered as plane. The coordinate space that we will consider is defined by the South (y, vertical axis) and East (x, horizontal axis) walls of the basin. Due to the very slow dynamics of the robot, the depth regulation algorithm is very simple: it is a three state controller. If the submarine is below the desired depth, the vertical thruster is turned on at its maximal speed. If the submarine is near the desired depth, it is off. If the submarine is above, the thruster is turned on in the other direction. Because going in the right direction at the right place is a key part to succeed in several tasks, the orientation and distance regulations are a little bit more complicated and are related because they control both the 2 horizontal thrusters. We used experimental methods to set these regulations. In some cases, the input of these regulations can be directly the output of sensors, in other cases algorithms must be used to process the sensors data and provide a right input. Here is what provides our sensors (Figure 23): Pressure sensor: the depth with respect to the surface. 360 degrees rotating sonar: an image of all that is around the robot, up to a range of 100 m. With this device, we get easily the distance to the first obstacle at a specific angle. IMU: the Euler angles of the robot, the rotating speeds (using inertial sensors), the accelerations and the magnetic field (that should indicate the direction to the North if there are no perturbations) in 3D. As the basin does not move, we get easily the orientation of the submarine with respect to the basin (and therefore the orientation of our submarine in the coordinate space we defined). But the accelerations are not really usable in our case (our submarine does too low accelerations). Bottom and front cameras: pictures of the sea floor or the front of the robot. 14

15 SAUC-E 2010 Journal Paper ENSIETA 15 Figure 23: Localization and detection Additional sensors could have been useful: Several acoustic devices to detect the intensity of the pinger signal: could give an idea of the distance and angle of the pinger with respect to the submarine (and therefore to the center of the basin, or Start 2). Drawbacks: too expensive or difficult to find or it would have taken time to make them ourselves. Doppler Velocity Loch (DVL): to get the speed and altitude with respect to the sea floor. Drawbacks: too expensive, might be too big and heavy. Front sonar: to get an image of the sea floor in front of the robot, to follow the pipeline for example. Drawbacks: too expensive. Lateral sonar: to get an image of the sea floor in the left or right of the robot. Drawbacks: too expensive. Several processing algorithms were also made available as inputs for the regulations: Camera image processing: o Color selection [2]. o Simple shapes detection (lines, circles, rectangles...). o Movement detection (if the submarine does not move and we know the target object changes over time) by comparison between successive pictures. o Interest points detection (can be a line, an object, a part of object or anything that could be singular and detectable in several pictures). For example, we can get the depth if we see the pipeline with the bottom camera and know its size and the characteristics of the camera. We could also try to keep a specific height, angle or distance with respect to the mid-water target by trying to keep it in the center of the front webcam picture and measure its width on the picture. Sonar image processing: o Ball, pipeline, wall and corner detection. For example, we can get the depth if we know that the size, the presence of objects or the distance between objects depends on the depth of the submarine (for example the pipeline should be visible with our sonar only when the submarine is close to the sea floor). We could also try to keep a specific angle and distance with respect to the mid-water target. 15

16 SAUC-E 2010 Journal Paper ENSIETA 16 Static localization: o Robust static localization using interval arithmetic ([3], [4]): it takes the dimension, the shape of the basin and any other singular feature (as a list of segments and circles) as input and uses the sonar and optionally the IMU to get the position of the submarine in the basin. Any object detected by the sonar that does not correspond to the input is considered as outlier. Dynamic localization: o Open loop on the control of the thrusters: taking into account experiments on acceleration time at start, average speed and deceleration time, we can evaluate the distance covered by the robot from one point to another. o Robust dynamic localization using interval arithmetic: it takes the dimension, the shape of the basin and any other singular feature (as a list of segments and circles) as well as a dynamics model of the movement of the submarine as input and uses the sonar and optionally the IMU to get the position of the submarine in the basin. Any object detected by the sonar that does not correspond to the input is considered as outlier. A sonar image processing algorithm (Figure 24) launched in the beginning when the submarine is stopped could automatically discover the environment of the robot (and therefore the shape and dimensions of the basin), assuming that the sonar can see some interests points (like the walls of the basin). This would be a kind of SLAM (Simultaneous Localization and Mapping) if it is used as input of the localization algorithms (that needs the dimension, the shape of the basin and any other singular feature) moreover if the environment discovery step is repeated several times to improve the trajectory estimation. Figure 24: Matching between sonar pings and the basin walls Some algorithms can provide different values for the same data (depth, orientation in the coordinate space, angle with respect to the mid-water target, distance to a waypoint in the coordinate space, distance to the mid-water target...) in the same time. For example, the camera image processing and sonar image processing algorithms can return different distances to the mid-water target. To handle that, all of the results of the sensors and algorithms are returned as intervals ([1]). A simple intersection between the results that evaluate the same data leads to 1 interval (more precise) for each data. The center of the interval is taken as input for the corresponding regulation. 16

17 SAUC-E 2010 Journal Paper ENSIETA 17 V. Innovation This year, the main innovation we would like to show during the SAUC-E competition is the idea of using several collaborating robots to accomplish tasks autonomously. Additionally, if we manage to use successfully our localization algorithm (static and dynamic) that use interval methods to compute the position of the submarine in a robust manner during the competition, it would be a good contribution to show that interval arithmetic can be successfully used in autonomous submarine robots. 17

18 SAUC-E 2010 Journal Paper ENSIETA 18 VI. Financial summary We got this year for the project. Products Prices ( ) Purpose 4 ASUS EeePC T91MT 2000 Embedded computers 2 Analog webcams ALLWAN AL- 900 Waterproof cameras Webcams HD Logitech Webcam 700 Webcams used for tests and in replacement Pro 9000 Various media readers, storage and 500 converters and various tools IP68 waterproof connectors 1000 Pressure sensor Keller 600 In replacement in case of problem D-Link DWL-2100AP High Speed 100 In replacement in case of problem Wireless Access Point Labjack UE9 400 In replacement in case of problem Servo controllers Robbe Rokraft 600 In replacement in case of problem SEABOTIX thrusters SBT In replacement in case of problem Trip 5000? 18

19 SAUC-E 2010 Journal Paper ENSIETA 19 VII. Risk assessment Risk Loss of control Recovery needed Sharp edges Frontal collision with a wall Electric shock Thrusters hazard Precaution Power switch, positively buoyant Central lifting cord Visible colors and diving gloves Bumper in front of the frontal webcam Only low voltages and intensities Propeller protected 19

20 SAUC-E 2010 Journal Paper ENSIETA 20 VIII. References [1] L. Jaulin, M. Kieffer, O. Didrit and E. Walter, Applied Interval Analysis with Examples in Parameter and State Estimation, Robust Control and Robotics, Springer-Verlag, 2001, ISBN: , [2] S. Bazeille, Vision sous-marine monoculaire pour la reconnaissance d'objets, Ph.D. Thesis, Université de Bretagne Occidentale, 2008, and other related work, [3] L. Jaulin, Robust set membership state estimation, Automatica, Volume 45, Issue 1, January 2009, Pages , [4] J. Sliwka, F. Le Bars, O. Reynet, L. Jaulin, Reconnaissance de forme pour la localisation de robots, submitted to RFIA 2010, 2009, France, 20