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We have proposed a cloud robotics architecture to address the constraints faced by current networked robots

Cloud robotics: architecture, challenges and applications

IEEE Network, no. 3 (2012): 21-28

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摘要

We extend the computation and information sharing capabilities of networked robotics by proposing a cloud robotic architecture. The cloud robotic architecture leverages the combination of an ad-hoc cloud formed by machine-to-machine (M2M) communications among participating robots, and an infrastructure cloud enabled by machine-to-cloud (M...更多

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简介
  • The authors extend the computation and information sharing capabilities of networked robotics by proposing a cloud robotic architecture.
  • Industrial robots have been widely deployed in factories to do tedious, repetitive, or dangerous tasks, such as assembly, painting, packaging, and welding.
  • These preprogrammed robots have been very successful in industrial applications due to their high endurance, speed, and precision in structured factory environments.
  • To extend the functional range of these robots or to deploy them in unstructured environments, robotic technologies are integrated with network technologies to foster the emergence of networked robotics
重点内容
  • We extend the computation and information sharing capabilities of networked robotics by proposing a cloud robotic architecture
  • To extend the functional range of these robots or to deploy them in unstructured environments, robotic technologies are integrated with network technologies to foster the emergence of networked robotics
  • We describe a cloud robotics architecture, some of the technical challenges, and its potential applications
  • We focus on the following three elastic computing models (Fig. 3): Peer-Based Model: each robot or virtual machine (VM) in the ubiquitous cloud is considered as a computing unit
  • We have proposed a cloud robotics architecture to address the constraints faced by current networked robots
  • Applications that can benefit from the cloud robotics approach are myriad and includes simultaneous localization and mapping, grasping, navigation, and many others that we have not discussed, like weather monitoring, intrusion detection, surveillance, and formation control
结论
  • Cloud robotics allows robots to share computation resources, information and data with each other, and to access new knowledge and skills not learned by themselves.
  • This opens a new paradigm in robotics that the authors believe leads to exciting future developments.
  • Applications that can benefit from the cloud robotics approach are myriad and includes SLAM, grasping, navigation, and many others that the authors have not discussed, like weather monitoring, intrusion detection, surveillance, and formation control
表格
  • Table1: Comparisons of different computing models
  • Table2: Comparisons of worst-case communication delays for different elastic computing models
Download tables as Excel
基金
  • Extends the computation and information sharing capabilities of networked robotics by proposing a cloud robotic architecture
  • Proposes and evaluate communication protocols, and several elastic computing models to handle different applications
  • Describes a cloud robotics architecture, some of the technical challenges, and its potential applications
  • Addresses technical challenges in designing and operating the cloud robotics architecture
  • Proposes the use of gossip protocols for M2M/M2C communications in cloud robotics
引用论文
  • B. Siciliano and O. Khatib, Eds., Springer Handbook of Robotics, Springer, 2008.
    Google ScholarLocate open access versionFindings
  • IEEE Society of Robotics and Automation’s Technical Committee on Networked Robots, available: http://www-users.cs.umn.edu/~isler/tc/
    Findings
  • P. Jacquet et al., “Optimized Link State Routing Protocol for Ad Hoc Networks,” Multi Topic Conf. 2001, IEEE INMIC 2001, Technology for the 21st Century, Proc. IEEE Int’l., 2001, pp. 62–68.
    Google ScholarLocate open access versionFindings
  • C. Perkins et al., “Performance Comparison of Two On-Demand Routing Protocols for Ad Hoc Networks,” IEEE Personal Commun., vol. 8, no. 1, Feb. 2001, pp. 16–28.
    Google ScholarLocate open access versionFindings
  • P. Mell and T. Grance, “The Nist Definition of Cloud Computing,” NIST Special Publication 800-145, Sept. 2011, available: http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf.
    Locate open access versionFindings
  • Google cloud robotics, available: http://googlemonthly.com/google-directions/google-io-2011-cloud-robotics.html.
    Findings
  • R. Arumugam et al., “DAvinCi: A Cloud Computing Framework for Service Robots,” Int’l. Conf. Robotics and Automation, 2010, pp. 3084– 3089.
    Google ScholarLocate open access versionFindings
  • D. Shah, “Gossip Algorithms,” Foundations and Trends in Networking, 2008, vol. 3, no. 1.
    Google ScholarLocate open access versionFindings
  • J. M. Rabaey, Ed., Digital Integrated Circuits, Prentice Hall, 1996.
    Google ScholarFindings
  • Y. Wen, W. Zhang, and H. Luo, “Energy-Optimal Mobile Application Execution: Taming Resource-Poor Mobile Devices With Cloud Clones,” Proc. 31st IEEE Int’l. Conf. Comp. Commun., Mar. 2012.
    Google ScholarLocate open access versionFindings
  • D. W. Soh, T. Q. S. Quek, and W. P. Tay, “Randomized Broadcast in Dynamic Network Environments,” Proc. IEEE Int’l. Wksp. Signal Proc. Advances for Wireless Commun., June 2011.
    Google ScholarLocate open access versionFindings
  • M. Waibel et al., “Roboearth — A World Wide Web for Robots,” IEEE Robotics & Automation Mag., vol. 18, no. 2, June 2011, pp. 69–82.
    Google ScholarLocate open access versionFindings
  • H. Durrant-Whyte and T. Bailey, “Simultaneous Localization and Mapping: Part I,” IEEE Robotics & Automation Mag., vol. 13, 2006, pp. 99–110.
    Google ScholarLocate open access versionFindings
  • C. Goldfeder and P. K. Allen, “Data-Driven Grasping,” Autonomous Robots, vol. 31, no. 1, pp. 1–20, Apr. 2011.
    Google ScholarLocate open access versionFindings
  • F. Bonin-Font, A. Ortiz, and G. Oliver, “Visual Navigation for Mobile Robots: A Survey,” J. Intelligent and Robotic Systems, vol. 53, 2008, pp. 263–96. GUOQIANG HU [M] (gqhu@@ntu.edu.sg) is an Assistant Professor in the School of Electrical and Electronics Engineering at Nanyang Technological University in Singapore. Prior to his current position, he was a postdoc research associate at University of Florida in 2008 and an assistant professor at Kansas State University from 2008 to 2011. He received his B.Eng, M.Phil, and Ph.D. degrees from University of Science and Technology of China, the Chinese University of Hong Kong, and University of Florida in 2002, 2004, and 2007, respectively. His research interest is in the analysis, control, and design of distributed intelligent systems.
    Google ScholarLocate open access versionFindings
  • WEE PENG TAY [M] (wptay@ntu.edu.sg) is an Assistant Professor in the School of Electrical and Electronics Engineering at Nanyang Technological University in Singapore. He received the BS degree in Electrical Engineering and Mathematics, and the M.S. degree in Electrical Engineering from Stanford University in 2002. He received the Ph.D. degree in Electrical engineering and Computer science from the Massachusetts Institute of Technology in 2008. His main research interests are in distributed signal processing and algorithms, data fusion and decision making in ad hoc networks, machine learning and applied probability.
    Google ScholarLocate open access versionFindings
  • YONGGANG WEN [M] (ygwen@ntu.edu.sg) is an Assistant Professor in the School of Computer Engineering at Nanyang Technological University (NTU) in Singapore. Prior to his present position, he has held R&D positions in networking companies in the USA, including Cisco and Lucent. He received his Ph.D. degree in electrical engineering and computer science from Massachusetts Institute of Technology (MIT) in 2008, his M.Phil. degree in information engineering from Chinese University of Hong Kong (CUHK) and B.Eng. degree in electronic engineering and information science from University of Science and Technology of China (USTC) in 2001 and 1999, respectively. His research interests are in cloud computing, content networking and green networks.
    Google ScholarLocate open access versionFindings
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