A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-03413-3_26In this work is presented a general architecture for a multi physical agent network system based on the coordination and the behaviour management. The system is organised in a hierarchical structure where are distinguished the individual agent actions and the collective ones linked to the whole agent network. Individual actions are also organised in a hybrid layered system that take advantages from reactive and deliberative control. Sensing system is involved as well in the behaviour architecture improving the information acquisition performance.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under the CICYT project Mission Based Control (COBAMI): DPI2011-28507-C02-02, under coordinated project High Integrity Partitioned Embedded Systems (Hi-PartES): TIN2011-28567-C03-03, and under the collaborative research project supported by the European Union MultiPARTES Project: FP7-ICT 287702. 2011-14.Muñoz Alcobendas, M.; Munera Sánchez, E.; Blanes Noguera, F.; Simó Ten, JE. (2013). A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control. En ROBOT2013: First Iberian Robotics Conference: Advances in Robotics, Vol. 1. Springer. 363-380. https://doi.org/10.1007/978-3-319-03413-3_26S363380Aragues, R.: Consistent data association in multi-robot systems with limited communications. Robotics: Science and Systems, 97–104 (2010)Aragues, R., Cortes, J., Sagues, C.: Distributed consensus on robot networks for dynamically merging feature-based maps. IEEE Transactions on Robotics (2012)Arkin, R.C.: Motor schema based mobile robot navigation. The International Journal of Robotics Research 8(4), 92–112 (1989)Asama, H., Habib, M.K., Endo, I., Ozaki, K., Matsumoto, A., Ishida, Y.: Functional distribution among multiple mobile robots in an autonomous and decentralized robot system. In: Proceedings of the 1991 IEEE International Conference on Robotics and Automation. IEEE (1991)Benet, G., Blanes, F., Martínez, M., Simó, J.: A multisensor robot distributed architecture. In: IFAC Conference INCOM 1998 (1998)Brooks, R.: A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2(1), 14–23 (1986)Canas, J.M., Matellán, V.: Dynamic schema hierarchies for an autonomous robot. In: Garijo, F.J., Riquelme, J.-C., Toro, M. (eds.) IBERAMIA 2002. 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In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, pp. 690–695 (2009)Jayasiri, A., Mann, G.K.I., Gosine, R.G.: Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(5), 1224–1238 (2011)Koenig, N., Howard, A.: Gazebo-3d multiple robot simulator with dynamics. Technical report (2006)Lin, F., Ying, H.: Modeling and control of fuzzy discrete event systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 32(4), 408–415 (2002)Madden, J.D.: Multi-robot system based on model of wolf hunting behavior to emulate wolf and elk interactions. In: 2010 IEEE International Conference on Robotics and Biomimetics, ROBIO, pp. 1043–1050 (2010)Mataric, M.J.: Interaction and intelligent behavior. Technical report, DTIC Document (1994)Olivera, V.M., Molina, J.M., Sommaruga, L., et al.: Fuzzy cooperation of autonomous robots. In: Fourth International System on Intelligent Robotics Systems, Lisboa, Portugal (1996)McGann, C., Py, F., Rajan, K., Thomas, H., Henthorn, R., McEwen, R.: A deliberative architecture for auv control. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 1049–1054. IEEE (2008)Munera, E., Muñoz, M., Simó, J., Blanes, F.: Humanoid Robot Self-Location In SPL League. In: Comité Español de Automática (CEA), XXXIII Jornadas de Automatica, 797–804 (2012)Proetzsch, M., Luksch, T., Berns, K.: Development of complex robotic systems using the behavior-based control architecture iB2C. Robotics and Autonomous Systems 58(1), 46–67 (2010)Qiu, D.: Supervisory control of fuzzy discrete event systems: a formal approach. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 35(1), 72–88 (2005)Aladebaran Robotics. NAO Software Documentation 1.12. 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Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Experiments in cooperative human multi-robot navigation

In this paper, we consider the problem of a group of autonomous mobile robots and a human moving coordinately in a real-world implementation. The group moves throughout a dynamic and unstructured environment. The key problem to be solved is the inclusion of a human in a real multi-robot system and consequently the multiple robot motion coordination. We present a set of performance metrics (system efficiency and percentage of time in formation) and a novel flexible formation definition whereby a formation control strategy both in simulation and in real-world experiments of a human multi-robot system is presented. The formation control proposed is stable and effective by means of its uniform dispersion, cohesion and flexibility

Development of personal area network (PAN) for mobile robot using bluetooth transceiver

The work presents the concept of providing a Personal Area Network (PAN) for microcontroller based mobile robots using Bluetooth transceiver. With the concept of replacing cable, low cost, low power consumption and communication range between 10m to 100m, Bluetooth is suitable for communication between mobile robots since most mobile robots are powered by batteries and have high mobility. The network aimed to support real-time control of up to two mobile robots from a master mobile robot through communication using Bluetooth transceiver. If a fast network radio link is implemented, a whole new world of possibilities is opened in the research of robotics control and Artificial Intelligence (AI) research works, sending real time image and information. Robots could communicate through obstacles or even through walls. Bluetooth Ad Hoc topology provides a simple communication between devices in close by forming PAN. A system contained of both hardware and software is designed to enable the robots to form a PAN and communicating, sharing information. Three microcontroller based mobile robots are built for this research work. Bluetooth Protocol Stack and mobile robot control architecture is implemented on a single microcontroller chip. The PAN enabled a few mobile robots to communicate with each other to complete a given task. The wireless communication between mobile robots is reliable based from the result of experiments carried out. Thus this is a platform for multi mobile robots system and Ad Hoc networking system. Results from experiments show that microcontroller based mobile robots can easily form a Bluetooth PAN and communicate with each other

Integration of Mobile Robot Navigation on a Control Kernel Middleware based system

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-07593-8_55This paper introduces how a mobile robot can perform navigation tasks by taking the advantages of implementing a control kernel middleware (CKM) based system. Smart resources are also included into the topology of the system for improving the distribution of computational load of the needed tasks. The CKM and the smart resources are both highly recon gurable, even on execution time, and they also implement.lt detection mechanisms and QoS policies. By combining of these capabilities, the system can be dinamically adapted to the requirements of its tasks. Furthermore, this solution is suitable for most type of robots, including those which are provided of a low computational power because of the distribution of load, the bene ts of exploiting the smart resources capabilities, and the dynamic performance of the system.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under the CICYT project Mission Based Control (COBAMI): DPI2011-28507-002-02.Munera Sánchez, E.; Muñoz Alcobendas, M.; Posadas-Yagüe, J.; Poza-Lujan, J.; Blanes Noguera, F. (2014). Integration of Mobile Robot Navigation on a Control Kernel Middleware based system. En Distributed Computing and Artificial Intelligence, 11th International Conference. Springer Advances in Intelligent Systems and Computing Volume 290. 477-484. https://doi.org/10.1007/978-3-319-07593-8_55S477484Rock (Robot Constrution Toolkit), http://www.rock-robotics.org/Albertos, P., Crespo, A., Simó, J.: Control kernel: A key concept in embedded control systems. In: 4th IFAC Symposium on Mechatronic Systems (2006)Bruyninckx, H., Soetens, P., Koninckx, B.: The Real-Time Motion Control Core of the Orocos Project. In: IEEE International Conference on Robotics and Automation, pp. 2766–2771 (2003)De Souza, G.N., Kak, A.C.: Vision for mobile robot navigation: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(2), 237–267 (2002)Fitzpatrick, P., Metta, G., Natale, L.: Towards long-lived robot genes. Robotics and Autonomous Systems (2008)Mohamed, N., Al-Jaroodi, J., Jawhar, I.: Middleware for robotics: A survey. In: 2008 IEEE Conference on Robotics, Automation and Mechatronics, pp. 736–742. IEEE (2008)Montemerlo, M., Roy, N., Thrun, S.: Perspectives on standardization in mobile robot programming: The carnegie mellon navigation (carmen) toolkit. In: Proceedings of 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), vol. 3, pp. 2436–2441. IEEE (2003)Muñoz, M., Munera, E., Blanes, J.F., Simo, J.E., Benet, G.: Event driven middleware for distributed system control. XXXIV Jornadas de Automatica, 8 (2013)Muñoz, M., Munera, E., Blanes, J.F., Simó, J.E.: A hierarchical hybrid architecture for mission-oriented robot control. In: Armada, M.A., Sanfeliu, A., Ferre, M. (eds.) First Iberian Robotics Conference of ROBOT 2013. AISC, vol. 252, pp. 363–380. Springer, Heidelberg (2014)Sánchez, E.M., Alcobendas, M.M., Noguera, J.F.B., Gilabert, G.B., Ten, J.E.S.: A reliability-based particle filter for humanoid robot self-localization in RoboCup Standard Platform League. Sensors (Basel, Switzerland) 13(11), 14954–14983 (2013)Poza-Luján, J.-L., Posadas-Yagüe, J.-L., Simó-Ten, J.-E.: Relationship between Quality of Control and Quality of Service in Mobile Robot Navigation. In: Omatu, S., De Paz Santana, J.F., González, S.R., Molina, J.M., Bernardos, A.M., Rodríguez, J.M.C. (eds.) Distributed Computing and Artificial Intelligence. AISC, vol. 151, pp. 557–564. Springer, Heidelberg (2012)Proetzsch, M., Luksch, T., Berns, K.: Development of complex robotic systems using the behavior-based control architecture iB2C. Robotics and Autonomous Systems 58(1), 46–67 (2010)Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: Ros: An open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3 (2009)Roy, N., Burgard, W., Fox, D., Thrun, S.: Coastal navigation-mobile robot navigation with uncertainty in dynamic environments. In: Proceedings of the 1999 IEEE International Conference on Robotics and Automation, vol. 1, pp. 35–40. IEEE (1999)Nicolau, V., Muñoz, M., Simó, J.: KertrolBot Platform: SiDiReLi: Distributed System with Limited Resources. Technical report, Institute of Control Systems and Industrial Computing - Polytechnic University of Valencia, Valencia, Spain (2011