Title: Fog Robotics for Efficient, Fluent and Robust Human-Robot Interaction,
Abstract: 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.