6 research outputs found

    Kinematics, motion analysis and path planning for four kinds of wheeled mobile robots

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    Multi-AGV transport of a load: state of art and centralized proposal

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    [EN] An automatic guided vehicle is a battery powered fully automated industrial transport system. These vehicles are widely used in the industrial sector to substitute manual forklifts and conveyors. The challenge of using AGVs as transport agents in industrial environments goes through providing them with enough intelligence to develop collaborative tasks. Among these collaborative tasks the multi-AGV transport of one object is differentiated from the multi-object multi-AGV transport. This work presents the state of art of cooperative transport solutions of one object between several AGVs. The theoretical fundaments are revised and several proposals for its resolution are classified and described. Finally, an own proposal of one-object multi-AGV transport with omnidirectional AGVs based on centralized remote control is presented.[ES] Un vehículo de guiado automático (Automatic Guided Vehicle –AGV-en inglés) es un sistema de transporte industrial completamente automatizado y alimentado por baterías. Estos vehículos son ampliamente utilizados en el sector industrial para sustituir a carretillas manuales y cintas transportadoras. El reto de la utilización de AGVs como agentes de transporte en entornos industriales pasa por dotarles de la inteligencia suficiente para desarrollar tareas colaborativas. Dentro de estas tareas colaborativas se diferencia el transporte multi-AGV de un objeto del transporte multi-AGV de múltiples objetos. Este trabajo presenta el estado del arte de las soluciones de transporte cooperativo de un objeto entre varios AGVs. Para ello, se revisan los fundamentos teóricos y se clasifican y describen varias propuestas para su resolución. Finalmente se propone una solución de control remoto centralizado para el transporte de una carga con AGVs omnidireccionales.Este trabajo ha sido apoyado parcialmente por la Junta de Castilla y León bajo el proyecto 10/16/BU/0014 y la empresa ASTI Mobile Robotics.Espinosa, F.; Santos, C.; Sierra-García, JE. (2020). Transporte multi-AGV de una carga: estado del arte y propuesta centralizada. Revista Iberoamericana de Automática e Informática industrial. 18(1):82-91. https://doi.org/10.4995/riai.2020.12846OJS8291181Adăscăliţei, F., and Doroftei, I. 2011. Practical Applications for Mobile Robots based on Mecanum Wheels - A Systematic Survey. The Romanian Review Precision Mechanics, Optics & Mechatronics, nº 40.Alonso-Mora, J., Barker, S. and Rus, D. 2017. Multi-robot formation control and object transport in dynamic environments via constrained optimization. The International Journal of Robotics Research. 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Control and Kinematic Design of Multi-Degree-ofFreedom Mobile Robots with Compliant Linkage. IEEE Trans. On Robotis and Automation. Vol. 1 I , nº I. https://doi.org/10.1109/70.345935Borenstein, J., 2000. The OmniMate: a guidewire and beacon-free AGV for highly reconfigurable applications. Int. Journal of Production Research. Vol. 38, nº 9, June 15, 2000. https://doi.org/10.1080/002075400188456Bostel, A.J. and Sagar, V,K. 1996. Dynamic control systems for AGVs. Engineering. https://doi.org/10.1049/cce:19960403Brown, R., and Jennings, J., 1995. A pusher/steerer model for strongly cooperative mobile robot manipulation. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots 3, 562-568Butdee, S., Vignat, F., Suebsomran, A. and Yarlagadda, P.K. 2009. Estimation and control of an automated guided vehicle. International Journal of Mechatronics and Manufacturing Systems 2(3). https://doi.org/10.1504/IJMMS.2009.026053Cameron, S. and Probert, P. 1994. Advanced Guided Vehicles: Aspects of the Oxford AGV Project. ISBN: 981-02-1393-X. https://doi.org/10.1142/2022Chen, X. and Li, Y., 2006. "Cooperative Transportation by Multiple Mobile Manipulators Using Adaptive NN Control". In 2006 International Joint Conference on Neural Networks.Chiacchio P. and Chiaverini S., 1997. Complex Robotic Systems. Springer. https://doi.org/10.1007/BFb0035182Choi, S.K., Easterday, O.T. 2001. An Underwater Vehicle Monitoring System and Its Sensors. Lecture Notes in Control and Information Sciences. Experimental robotics. Springer-Verlag. Pp551-560. ISBN 3-540-42104-1. https://doi.org/10.1007/3-540-45118-8_55Digani, V., Sabattini, L., Secchi, C., Fantuzzi, C., 2014. Hierarchical Traffic Control for Partially De-centralized Coordination of Multi AGV Systems in Industrial Environments. IEEE Inter-national Conference on Robotics & Automation (ICRA). https://doi.org/10.1109/ICRA.2014.6907764Esposito, J. M., Feemster, M. G., Smith, E., 2008. Cooperative manipulation on the water using a swarm of autonomous tugboats. in Proc. 2008 IEEE Int. Conf. on Robotics and Automation, pp. 1501-1506. https://doi.org/10.1109/ROBOT.2008.4543414Habibi, G., Kingston, Z., Xie, W., Jellins, M., McLurkin, J., 2015. Distributed Centroid Estimation and Motion Controllers for Collective Transport by Multi-Robot Systems. IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/ICRA.2015.7139356Seattle, Washington Hasimoto, M. and Oba, F., 1993. Dynamic control approach for motion coordination of multiple wheeled mobile robots transporting a single object. Proceedings of the 1993 IEEE./RSJ lntemational Conference on lntelligent Robots and Systems Yokohama, Japan July 26-30, 1993Hichri, B., Adouane, L., Fauroux, J.C., Mezouar, Y. and Doroftei, I. Cooperative Mobile Robot Control Architecture for Lifting and Transportation of Any Shape Payload. Chapter book of Distributed Autonomous Robotic Systems pp 177-191. ISBN 978-4-431-55877-4. https://doi.org/10.1007/978-4-431-55879-8_13Hirata, Y., Kosuge, K., 2001. Motion Control of Distributed Robot Helpers Transporting a Single Object in Cooperation with a Human. Lecture Notes in Control and Information Sciences. Experimental robotics. SpringerVerlag. Pp. 313-322. ISBN 3-540-42104-1 https://doi.org/10.1007/3-540-45118-8_32Karim, N.A. and Ardestani, M.A. 2016. Takagi-Sugeno Fuzzy formation control of non-holonomic robots. 4th International Conference on Control, Instrumentation, and Automation (ICCIA), Qazvin, 2016, pp. 178-183. https://doi.org/10.1109/ICCIAutom.2016.7483157Kosuge, K., Oosumi, T., 1996. Decentralized Control of Multiple Robots Handling an Object. Proc. Of 1996 IEEE Int. Conf. on Intelligent Robots and Systems, pp.318-323.Kosuge, K., Sato., M., 1999. Transportation of a Single Object by Multiple Decentralized- Controlled Nonholonomic Mobile Robots. Proceedings of the 1999 IEEVRSJ International Conference on Intelligent Robots and Systems.Krnjak, A., and others. 2015. Decentralized control of free ranging AGVs in warehouse environments. IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/ICRA.2015.7139465Li, P.Y., 1999. Adaptive Passive Velocity Field Control. American Control Conference. June, 1999. https://doi.org/10.1109/ACC.1999.783145Li, P.Y., Horowitz, R., 2001. Passive Velocity Field Control (PVFC): Part I, Geometry and Robustness. IEEE Trans on Automatic Control. Vol 46, no 9. https://doi.org/10.1109/9.948463Li, P.Y., Horowitz, R., 2001. Passive Velocity Field Control (PVFC): Part II, Application to contour following. IEEE Trans on Automatic Control. Vol 46, no 9, 2001. https://doi.org/10.1109/9.948464Liu, Z., Hou, L., Shi, Y., Zheng X., Teng, H., 2018. A co-evolutionary design methodology for complex AGV system. Neural Computing and Applications 29:959-974. Springer. https://doi.org/10.1007/s00521-016-2495-1Meissner, H., Ilsen, R. and Aurich, J.C. 2017. Analysis of control architectures in the context of Industry 4.0. Proc CIRP 2017; 62:165-9. https://doi.org/10.1016/j.procir.2016.06.113Mellinger, D., Shomin, M., Michael, N., Kumar, V., 2010. Cooperative grasping and transport using multiple quadrotors. in Proc. Distributed Autonomous Robotic Systems, Lusanne, pp 545-558. https://doi.org/10.1007/978-3-642-32723-0_39Neumann, M.A., Chin, M.H., Kitts, C.A., 2014. Object Manipulation through Explicit Force Control Using Cooperative Mobile Multi-Robot Systems" Proceedings of the World Congress on Engineering and Computer Science 2014 Vol I WCECS 2014, 22-24 October, 2014, San Francisco, USAOhashi, F., Kaminishi, K., Figueroa, J.D., Kato, H., Ogata, T., Hara T., Ota, J., 2016. 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Springer. https://doi.org/10.1007/s00521-016-2495-1Pereira, G.A.S., Pimentel, B.S., Chaimowicz, L., Campos, M.F.M., 2002. Coordination of multiple mobile robots in an object carrying task using implicit communication. Proceedings of the 2002 IEEE International Conference on Robotics & Automation" May 2002. https://doi.org/10.1109/ROBOT.2002.1013374Quinn, M., 2004. The evolutionary design of controllers for minimallyequipped homogeneous multi-robot systems. Ph.D. thesis. Brighton: University of SussexReister, D. B., 1991. A New Wheel Control System for the Omnidirectional HERMIES-III Robot. Proceedings of the IEEE Conference on Robotics and Automation Sacramento, California, April 7-12, pp. 2322-2327.Ria, 2019. Robotic Industries Association. "Logistic Robots" https://www.robotics.org/service-robots/logistics-robots, available on June 7th, 2019.Saha, S.K. and Angeles, J. 1989. Kinematics and dynamics of a three-wheeled 2-DOF AGV. ICRA 1989. https://doi.org/10.1109/ROBOT.1989.100202Santos, C., Espinosa, F., Martinez-Rey, M., Gualda, D. and Losada, C. 2019. Self-Triggered Formation Control of Nonholonomic Robots. Sensors 2019, 19(12), 2689; https://doi.org/10.3390/s19122689Solaque, L.E., Avendaño, D.R., Molina, M.A., Pulido, C.A. 2015. Sistema de transporte cooperativo desarrollado para un grupo de robots móviles noholonómicos usando el método Líder Virtual. Congreso internacional 264 de ingeniería mecatrónica y automatización - CIIMA 2015Suh, J.H., Lee, Y.J., Lee, K.S., 2005. Object-transportation control of cooperative AGV systems based on virtual-passivity decentralized control algorithm. Journal of Mechanical Science and Technology. Vol 19 n09, pp. 1720-1735. https://doi.org/10.1007/BF02984184Tan, W. 2002. Modeling and Control Design of an AGV. Proceedings of the 41st IEEE Conference on Decision and Control. 2002. https://doi.org/10.1109/CDC.2002.1184623Tuci, E., Alkilabi, M. H., & Akanyeti, O., 2018. Cooperative Object Transport in Multi-robot Systems: A Review of the State-of-the-Art. Frontiers in Robotics and AI. https://doi.org/10.3389/frobt.2018.00059Ullrich, G., 2015. Automated Guided Vehicle Systems. A Primer with Practical Applications. Springer. ISBN 978-3-662-44813-7 DOI 10.1007/978-3-662-44814-4Wada, M. 1996. Holonomic and omnidirectional vehicle with conventional tires. IEEE Int. Conference on Robotics and Automation. May, 1996.Wada, M., Torii, R., 2013. Cooperative transportation of a single object by omnidirectional robots using potential method. 16th International Conference on Advanced Robotics (ICAR). https://doi.org/10.1109/ICAR.2013.6766543Wang, Z., Nakano, E., and Matsukawa, T., 1994. Cooperating multiple behavior based robots for object manipulation. in Proc. of the IEEE/RSJ/GI Int. Conf. on Intelligent Robots and Systems, Vol. 3 1524-1531 https://doi.org/10.1007/978-4-431-68275-2_33Wang, 2016 Z. Wang and M. Schwager. Chapter book: "Multi-robot manipulation without communication". Book: Distributed autonomous robotic systems. Editors: N.Y. Chong and Y.J. ISBN 978-4-431-55877-4 DOI 10.1007/978-4-431-55879-8Wang, T.M., Tao, Y., Liu, H., 2018. Current researches and future development trend of intelligent robot: a review. International Journal of Automation & Computing. Vol 15, no 5, pp. 525-548. https://doi.org/10.1007/s11633-018-1115-1Yan, Z., Jouandeau, N., and Cherif, A. A., 2013. A Survey and Analysis of Multi-Robot Coordination. Int. Journal of Advanced Robotic Systems 10 (12), 399. https://doi.org/10.5772/57313Yang, X., Watanabe, K., Kiguchi, K., Izumi, K., 2003. Coordinated transportation of a single object by two nonholonomic mobile robots. Artif Life Robotics. ISAROB 2003. https://doi.org/10.1007/BF02480885Yufka, A., Ozkan, M., 2015. Formation-based Control Scheme for Cooperative Transportation by Multiple Mobile Robots. 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    Design And Implementation Of An Omnidirectional Mobile Robot Platform

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    Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2008Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2008Bu çalısmada robotik alanında yapılan akademik çalısmaların genis bir bölümünde uygulama gelistirme platformu olarak kullanılmak üzere; gerekli islemci gücü, algılama yetileri, hareket kabiliyeti ve iletisim altyapılarını sunan bir mobil robot platform tasarlanmıs ve gerçeklenmistir. Gerçeklenen robotun tabanı, iki diferansiyel sürümlü platformun üzerine sabitlenmistir. Bu sayede serbestlik derecesi dört olan taban, diferansiyel sürümlü platformları kontrol ederek her yöne hareket edebilme yeteneğine sahiptir. Gerçeklenen mekanik tasarımda, odometri tabanlı hassas konumlandırmanın mümkün olabilmesi için, robotun tasarımının kendine has geometrik avantajlarını kullanarak odometri hatalarının azaltılmasına olanak veren bir yöntem sunulmustur. Hareketli platformun üzerindeki donanım bataryalar, üç eksende hareketli bir kamera, çift çekirdekli bir DSP sistemi, Linux tabanlı bir kontrol kartı, kablosuz ağ ve video bağlantısı, grafik LCD ve detayları sunulmus olan, iki eksende hareketli bir lazer isaretçi ile kameranın kullanıldığı, çalısmaya özel olarak gelistirilmis üç boyutlu mesafe ölçerinden olusmaktadır.In this study, an omnidirectional mobile robot with sufficient processing power, sensory units and communication facilities for being utilized as an application development platform for a wide range of academic research in the field of robotics was designed and implemented. The base plane of the robot is attached onto two differential drive platforms, giving four-degrees-of-freedom to the base. This makes the robot able to move to any direction with proper control of the differential drive platforms, giving the property of omnidirectionality. A method to reduce odometric errors and make odometry based accurate positioning possible was also presented which utilizes the geometrical advantages particular to the robot’s mechanic design. The hardware on the moving base consists of batteries, a camera moving in three axes, a dual core DSP system, a Linux based control card, wireless network and video connection, graphical LCD and a laser pointer moving in two axes. An algorithm that uses the laser and the camera to obtain three dimensional distance measurements was also derived.Yüksek LisansM.Sc

    Engineering Physics and Mathematics Division progress report for period ending December 31, 1994

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    Self–organised multi agent system for search and rescue operations

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    Autonomous multi-agent systems perform inadequately in time critical missions, while they tend to explore exhaustively each location of the field in one phase with out selecting the pertinent strategy. This research aims to solve this problem by introducing a hierarchy of exploration strategies. Agents explore an unknown search terrain with complex topology in multiple predefined stages by performing pertinent strategies depending on their previous observations. Exploration inside unknown, cluttered, and confined environments is one of the main challenges for search and rescue robots inside collapsed buildings. In this regard we introduce our novel exploration algorithm for multi–agent system, that is able to perform a fast, fair, and thorough search as well as solving the multi–agent traffic congestion. Our simulations have been performed on different test environments in which the complexity of the search field has been defined by fractal dimension of Brownian movements. The exploration stages are depicted as defined arenas of National Institute of Standard and Technology (NIST). NIST introduced three scenarios of progressive difficulty: yellow, orange, and red. The main concentration of this research is on the red arena with the least structure and most challenging parts to robot nimbleness

    Proceedings of the NASA Conference on Space Telerobotics, volume 1

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    The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty
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