2012 IEEE/RSJ International Conference on Intelligent Robots and Systems October 7-12, 2012. Vilamoura, Algarve, Portugal
Operations with Multiple Unmanned Systems Hugo Dias, Pedro Calado, Ricardo Bencatel, Ricardo Gomes, Sergio Ferreira, and Jo˜ao Sousa
Abstract— In the video we present results obtained from experiments we ran with multiple unmanned vehicles. The vehicles used in the experiments were made in the LSTS, which is introduced in the beginning of the video. A formation control problem using an Autonomous Surface Vehicle and an Autonomous Underwater Vehicle is presented first, then followed by a multiple Unmanned Aerial Vehicles control problem. After both problems an approach is proposed and results are presented.
I. E XTENDED S UMMARY The LSTS, or Underwater Systems and Technology Laboratory is a research laboratory in the University of Porto in Portugal. The areas of research revolve around unmanned systems such as Autonomous Underwater Vehicles (AUV), Autonomous Surface Vehicles (ASV), Unmanned Aerial Vehicles (UAV) and Remotely Operated Vehicles (ROV), [1], [2], [3], [4]. Besides manufacturing these, we also do the communication gateways that enable operators to access and send commands to the vehicles. The software running onboard the systems, the operator console software and the communications protocol are all written in the lab. A. The Vision of the LSTS The longer term goal of the LSTS is to create an heterogeneous network where autonomous vehicles can be used as mobile nodes. Operators will be able to control more than one vehicle at the same time and they will function as data mules by conveying data from one node to the other. Ideally, the operator will be able to, for instance, transparently receive data from an AUV that is outside of communication range, by using an UAV to collect and upload the data. In order for a network such as this one to work 24/7, vehicles and operators will be easily added and removed from mesh. Making lack of fuel and fatigue problems easier to deal with. B. The LSTS Toolchain All the vehicles built in the LSTS, and the gateways, run the same software toolchain, which comprises the onboard software, communications protocol and operator console software. Naturally, the software might be configured in a *The research leading to these results has received funding from the European Commission FP7-ICT Cognitive Systems, Interaction, and Robotics under the contract #270180 (NOPTILUS). 1 Faculty of Engineering, Porto University, R. Dr. Roberto Frias, s/n 4200-465 Porto, Portugal
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different way for an AUV and for an UAV, but it still the same piece of software. Onboard every unmanned system we manufacture, there is a CPU running our onboard software, DUNE: Unified Navigation Framework, written in C++, [5]. It is responsible not only for every interaction with sensors, payload and actuators, but also for communications, navigation, control, maneuvering, plan execution and vehicle supervision. It is CPU architecture independent (Intel x86 or compatible, Sun SPARC, ARM, PowerPC and MIPS) as well as operating system independent (Linux, Solaris, Apple Mac OS X, FreeBSD, NetBSD, OpenBSD, eCos, RTEM, Microsoft Windows 2000 or above and QNX Neutrino). Thanks to its modularity and versatility, DUNE does not only run in our ASVs, ROVs, AUVs and UAVs, but also in our Manta communication gateways, [6]. The IMC protocol [7] is a message-oriented protocol targeting networked vehicle and sensor operations. IMC defines a common message set that is understood by all systems and used for communication between network nodes, DUNE tasks and Neptus plug-ins. IMC is fully defined and documented in a single XML file which can be translated into different language bindings using XSLT. Neptus software is used by operators to visually plan, simulate, monitor and review missions executed by autonomous vehicles. Neptus provides user interfaces to control vehicles of different types like AUVs, UAVs, ASVs and heterogeneous teams of the former simultaneously [8]. C. Operations with Multiple Marine Vehicles In our operations at sea we used an ASV and an AUV to perform coordinated control, Swordfish and nAUV. The goal was too have them navigate along parallel paths, known a priori, maintaining the along track distance, between each other, as short as possible. If nAUV remained at the surface this could have been done solely by using wifi. However, we made the decision to use only the acoustic channel, since it represents a more relevant and realistic problem from the point of view of underwater vehicle control. Therefore, both the ASV and AUV were equipped with acoustic modems (manufactured by Benthos). We assured both were submerged at all times. Since nAUV relies on acoustic navigation (LBL) using another acoustic modem, the periods during which the the vehicles communicated were rather short (more or less during 2 seconds every 6 seconds). Message packets compliant with our communications protocol IMC were exchanged during these runs. They contained position data from each vehicle, that were used to compute the along track distance between them. This distance was
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used by a Sliding Mode based controller, implemented in DUNE, to compute speed commands (which are also IMC messages). Controlling speed allows controlling the along track distance and therefore attempting to minimize it. The technique used was based on [9]. Once Swordfish and nAUV were deployed, the operator drew a single path in Neptus which was used to generate both parallel paths seen in the videl. These paths (or plans as we call them) were then sent to the vehicles, specified as IMC messages. The order to start the plans was thrown, and the maneuvering started. The map feature in Neptus allows the operator(s) to track the vehicles’ positions as they move. Orders for stopping/aborting the plans can be thrown at any time, by using the wifi or acoustic link. The analysis of the collected data was done using Neptus Mission Review and Analysis (MRA) tool. All data collected is logged in the vehicle using IMC messages. MRA allows the operator to visualize these logs. Even though the amount of messages exchanged by the vehicles was quite short, they still managed to perform formation control and arrived to the last waypoint of their paths roughly at the same time. D. Operations with Multiple Unmanned Aerial Vehicles For the operations using our UAVs we considered 2 scenarios. In the first one we tracked a ground target through its GPS position and in the second one we executed a formation flight. We started by equipping an car with a GPS beacon. Both the car and the formation leader UAV were equipped with modules capable of GSM communications. During the tracking exercise a flight formation is maintained between both UAVs. To enable this feature both vehicles were equipped with wireless communication capabilities, so to allow them the ability of exchanging telemetry details, required for the formation coordination. Our Dune software is used as an active gateway, allowing the interaction between our C4I software Neptus and the autopilot, through a wireless network. While in the air the formation leader uses a path tracking algorithm to track a circular path over the moving target [10].
This algorithm combines the UAV position and the target position, generating the bank commands required to reduce the cross track error and maintain a constant distance to the target. The flight formation algorithm uses a Sliding Mode technique over a 2D space, i.e., the horizontal plane [11]. The controller includes a collision avoidance logic, which enables it to control tight formations and the formation form-up phase. The aircraft are controlled through bank and speed commands, which are generated by combining the formation aircraft information, and by compensating the aircraft formation dynamics through feedback linearization. R EFERENCES [1] L. Madureira, A. Sousa, J. B. Sousa, and G. M. Gonc¸alves, “Low cost autonomous underwater vehicles for new concepts of coastal field studies,” in 10th International Coastal Symposium (ICS 2009), 2009. [2] H. Ferreira, R. Martins, E. Marques, J. Pinto, A. Martins, J. Almeida, J. Sousa, and E. Silva, “Swordfish: an autonomous surface vehicle for network centric operations,” in OCEANS 2007 - Europe, june 2007, pp. 1 –6. [3] G. M. Gonc¸alves, E. Pereira, J. B. de Sousa, J. Morgado, R. Bencatel, J. Correia, and L. F´elix, “Unmanned air vehicles for coastal and environmental research,” april 2009. [4] R. Gomes, A. Martins, A. Sousa, J. Sousa, S. Fraga, and F. Pereira, “A new rov design: issues on low drag and mechanical symmetry,” in Oceans 2005 - Europe, vol. 2, june 2005, pp. 957 – 962 Vol. 2. [5] J. Pinto, P. Calado, J. Braga, P. Dias, R. Martins, E. Marques, and J. Sousa, “Implementation of a control architecture for networked vehicle systems,” in NGCUV 2012 - EUROPE, april 2012. [6] LSTS, “Manta user manual,” 2011. [Online]. Available: http://whale.fe.up.pt/manta/a300/Manta A300 User Manual r1.pdf [7] R. Martins, P. Dias, E. Marques, J. Pinto, J. Sousa, and F. Pereira, “Imc: A communication protocol for networked vehicles and sensors,” in OCEANS 2009 - EUROPE, may 2009, pp. 1 –6. [8] P. Dias, S. Fraga, R. Gomes, G. Gonc¸alves, F. Pereira, J. Pinto, and J. Sousa, “Neptus - a framework to support multiple vehicle operation,” in Oceans 2005 - Europe, vol. 2, june 2005, pp. 963 – 968 Vol. 2. [9] P. Calado and J. Sousa, “Leader-follower control of underwater vehicles over acoustic communications,” in OCEANS, 2011 IEEE Spain, june 2011, pp. 1 –6. [10] T. Oliveira and P. Encarnao, “Ground target tracking for unmanned aerial vehicles,” in AIAA Guidance, Navigation, and Control Conference, Toronto, Ontario, Canada, Aug. 2-5 2010. [11] R. Bencatel, M. Faied, J. Sousa, and A. Girard, “Formation control with collision avoidance,” in 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, Florida, USA, December 12-15 2011.
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