Fog robotics for efficient, fluent and robust human-robot interaction

Krishna Chand Gudi, SL; Ojha, S; Johnston, B; Clark, J; Williams, MA

Fog robotics for efficient, fluent and robust human-robot interaction

Krishna Chand Gudi, SL Ojha, S

Johnston, B Clark, J

Williams, MA

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Publication Type:: Conference Proceeding
Citation:: NCA 2018 - 2018 IEEE 17th International Symposium on Network Computing and Applications, 2018
Issue Date:: 2018-11-26

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Field	Value	Language
dc.contributor.author	Krishna Chand Gudi, SL	en_US
dc.contributor.author	Ojha, S https://orcid.org/0000-0003-4856-8335	en_US
dc.contributor.author	Johnston, B	en_US
dc.contributor.author	Clark, J https://orcid.org/0000-0002-1920-341X	en_US
dc.contributor.author	Williams, MA https://orcid.org/0000-0002-1047-0503	en_US
dc.date.issued	2018-11-26	en_US
dc.identifier.citation	NCA 2018 - 2018 IEEE 17th International Symposium on Network Computing and Applications, 2018	en_US
dc.identifier.isbn	9781538676592	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133517
dc.description.abstract	© 2018 IEEE. Active communication between robots and humans is essential for effective human-robot interaction. To accomplish this objective, Cloud Robotics (CR) was introduced to make robots enhance their capabilities. It enables robots to perform extensive computations in the cloud by sharing their outcomes. Outcomes include maps, images, processing power, data, activities, and other robot resources. But due to the colossal growth of data and traffic, CR suffers from serious latency issues. Therefore, it is unlikely to scale a large number of robots particularly in human-robot interaction scenarios, where responsiveness is paramount. Furthermore, other issues related to security such as privacy breaches and ransomware attacks can increase. To address these problems, in this paper, we have envisioned the next generation of social robotic architectures based on Fog Robotics (FR) that inherits the strengths of Fog Computing to augment the future social robotic systems. These new architectures can escalate the dexterity of robots by shoving the data closer to the robot. Additionally, they can ensure that human-robot interaction is more responsive by resolving the problems of CR. Moreover, experimental results are further discussed by considering a scenario of FR and latency as a primary factor comparing to CR models.	en_US
dc.relation.ispartof	NCA 2018 - 2018 IEEE 17th International Symposium on Network Computing and Applications	en_US
dc.relation.isbasedon	10.1109/NCA.2018.8548077	en_US
dc.title	Fog robotics for efficient, fluent and robust human-robot interaction	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. Active communication between robots and humans is essential for effective human-robot interaction. To accomplish this objective, Cloud Robotics (CR) was introduced to make robots enhance their capabilities. It enables robots to perform extensive computations in the cloud by sharing their outcomes. Outcomes include maps, images, processing power, data, activities, and other robot resources. But due to the colossal growth of data and traffic, CR suffers from serious latency issues. Therefore, it is unlikely to scale a large number of robots particularly in human-robot interaction scenarios, where responsiveness is paramount. Furthermore, other issues related to security such as privacy breaches and ransomware attacks can increase. To address these problems, in this paper, we have envisioned the next generation of social robotic architectures based on Fog Robotics (FR) that inherits the strengths of Fog Computing to augment the future social robotic systems. These new architectures can escalate the dexterity of robots by shoving the data closer to the robot. Additionally, they can ensure that human-robot interaction is more responsive by resolving the problems of CR. Moreover, experimental results are further discussed by considering a scenario of FR and latency as a primary factor comparing to CR models.

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http://hdl.handle.net/10453/133517