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Cloud-based Robotic Systems for Intelligent Services

Submission Deadline: 1 May 2018

Submission Deadline: 1 May 2018

IEEE Access invites manuscript submissions in the area of Cloud-based Robotic Systems for Intelligent Services.

Recent advances in sensor/actuator as well as artificial intelligence (AI) technologies have made it possible for mobile robots such as autonomous automobiles and autonomous unmanned aerial vehicles to go about performing their tasks in varied environments. With wireless communications, these mobile robots can be connected to each other to exchange information, coordinate their movements, and cooperate to perform more extensive tasks, forming robotic systems. Using wireless communications, such robotic systems can further be connected to cloud computing services via the mobile Internet, which offers the potential to significantly enhance the capabilities of such robotic systems. Thus cloud-based robotic systems offer great promises for intelligent services beyond the capabilities of current robots or robotic systems.

First, robot systems employing advanced AI techniques that leverage multiple layer artificial neural networks for deep learning can enable intelligent services that learn from past experience to plan a course of actions that optimizes some task objectives, e.g., minimizing energy consumption, for the current environmental conditions. However, these machine learning techniques are computation intensive and may not be well supported by individual robotic systems. In contrast, cloud computing services offer virtually unlimited computation resources on-demand in a scalable manner, greatly facilitating the use of advanced AI techniques in robotic systems. Second, widespread deployment of robotic systems employing a large number of sensors results in a massive amount of data being generated over short periods of time. Cloud-based big data analytics can be employed to derive useful information to enhance the utility of cloud-based robotic systems. For example, applying big data analytics to data collected from a large number of cloud-based robotic systems, a manufacturer may be able to determine that a batch of sensors manufactured by this company is defective. Third, it is conceivable that in the future distributed general purpose robotic units connected to the cloud can be dynamically configured and programmed to form logical robotic systems under software control to perform specific services in a virtualized manner, i.e., cloud-based robotic systems can provide software-defined robotic system as a service. Cloud computing platforms would be crucial to enable a programming environment capable of fast service creation, as well as an operational and management environment to ensure that these intelligent robotic services can operate reliably and be properly managed.

Based on the above observations, we can see that cloud-based robotic systems offer great potential for intelligent services in both the short and longer term, but there are many technical challenges that need to be addressed. Some of the technical challenges and potential applications of cloud-based robotic systems include but are not limited to:

  1. Cloud-based big data analytics mechanisms;
  2. Cooperative mechanisms to coordinate the information of robotic systems and share updates on detected changes in the environment;
  3. Architectures, programming framework, management and control mechanisms to enable robotic function virtualization;
  4. Robotic edge computing to complement the cloud in satisfying hard real time interaction needs;
  5. Robot-assisted healthcare, especially for shut-in and elderly patients, with monitoring, diagnostic and simple treatment capabilities; by sampling data from sensors for body to the cloud system, using data mining and machine learning techniques;
  6. Smart homes, offices and factories equipped with cloud-based robotic systems for enhanced security, energy efficiency, work throughput, occupant comfort, etc.

The main objective of this Special Section in IEEE Access is to collect multidisciplinary research contributions on technological breakthrough and advancement towards cloud-based robotic systems for intelligent services. Topics explored in this Special Section include, but are not limited, to the following aspects of intelligent services involving cloud-based robotic systems:

  • Cloud computing technologies
  • Cooperative robotic systems
  • Multi-modal robotic cognition
  • Cooperative communications among robots
  • Real-time big data analytics of customers
  • Data mining techniques
  • Cloud architecture and cloud storage
  • Mobile social networks
  • Instance detection and recognition in robotic system
  • Image and scene classification in robotic system
  • Semantic interpretation in robotic system
  • Robot function virtualization
  • Robotic edge computing

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Associate Editor: Prof. Xiping Hu, Chinese Academy of Sciences, China

Guest Editors:

  1. Victor C.M. Leung, University of British Columbia, Canada
  2. Adnan Al-Anbuky, Auckland University of Technology, New Zealand
  3. Ken Goldberg, University of California, Berkeley, USA
  4. Hesheng Wang, Shanghai Jiao Tong University, China
  5. Fei Wang, Cornell University, USA
  6. Jianwei Zhang, University of Hamburg, German

 

Relevant IEEE Access Special Sections:

  1. Trends and Advances for Ambient Intelligence with Internet of Things Systems
  2. Big Data Analytics in Internet-of-Things and Cyber-Physical System
  3. Industry 4.0

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://mc.manuscriptcentral.com/ieee-access

For inquiries regarding this Special Section, please contact: xp.hu@siat.ac.cn