TY - JOUR
T1 - Revolutionizing Social Robotics
T2 - A Cloud-Based Framework for Enhancing the Intelligence and Autonomy of Social Robots †
AU - Elfaki, Abdelrahman Osman
AU - Abduljabbar, Mohammed
AU - Ali, Luqman
AU - Alnajjar, Fady
AU - Mehiar, Dua’a
AU - Marei, Ashraf M.
AU - Alhmiedat, Tareq
AU - Al-Jumaily, Adel
N1 - Funding Information:
The authors would also like to acknowledge the financial support for this work from the Deanship of Scientific Research (DSR) at the University of Tabuk, Tabuk, Saudi Arabia, under grant no. 1441–105.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/4
Y1 - 2023/4
N2 - Social robots have the potential to revolutionize the way we interact with technology, providing a wide range of services and applications in various domains, such as healthcare, education, and entertainment. However, most existing social robotics platforms are operated based on embedded computers, which limits the robot’s capabilities to access advanced AI-based platforms available online and which are required for sophisticated physical human–robot interactions (such as Google Cloud AI, Microsoft Azure Machine Learning, IBM Watson, ChatGPT, etc.). In this research project, we introduce a cloud-based framework that utilizes the benefits of cloud computing and clustering to enhance the capabilities of social robots and overcome the limitations of current embedded platforms. The proposed framework was tested in different robots to assess the general feasibility of the solution, including a customized robot, “BuSaif”, and commercialized robots, “Husky”, “NAO”, and “Pepper”. Our findings suggest that the implementation of the proposed platform will result in more intelligent and autonomous social robots that can be utilized by a broader range of users, including those with less expertise. The present study introduces a novel methodology for augmenting the functionality of social robots, concurrently simplifying their utilization for non-experts. This approach has the potential to open up novel possibilities within the domain of social robotics.
AB - Social robots have the potential to revolutionize the way we interact with technology, providing a wide range of services and applications in various domains, such as healthcare, education, and entertainment. However, most existing social robotics platforms are operated based on embedded computers, which limits the robot’s capabilities to access advanced AI-based platforms available online and which are required for sophisticated physical human–robot interactions (such as Google Cloud AI, Microsoft Azure Machine Learning, IBM Watson, ChatGPT, etc.). In this research project, we introduce a cloud-based framework that utilizes the benefits of cloud computing and clustering to enhance the capabilities of social robots and overcome the limitations of current embedded platforms. The proposed framework was tested in different robots to assess the general feasibility of the solution, including a customized robot, “BuSaif”, and commercialized robots, “Husky”, “NAO”, and “Pepper”. Our findings suggest that the implementation of the proposed platform will result in more intelligent and autonomous social robots that can be utilized by a broader range of users, including those with less expertise. The present study introduces a novel methodology for augmenting the functionality of social robots, concurrently simplifying their utilization for non-experts. This approach has the potential to open up novel possibilities within the domain of social robotics.
KW - autonomy
KW - cloud-based
KW - intelligence
KW - remote-control
KW - social robots
KW - teleoperation
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U2 - 10.3390/robotics12020048
DO - 10.3390/robotics12020048
M3 - Article
AN - SCOPUS:85153713843
SN - 2218-6581
VL - 12
JO - Robotics
JF - Robotics
IS - 2
M1 - 48
ER -
