雾天机器人：总结，挑战和未来范围
Fog Robotics: A Summary, Challenges and Future Scope
摘要：
人机交互对于使机器人更接近人类起着至关重要的作用。机器人通常受到自身能力的限制。因此，他们利用云机器人来提高他们的灵活性。它的能力包括共享地图、图像和处理能力等信息。整个过程涉及到分发数据，这些数据将大幅增长。可能出现新的问题，例如带宽、回程和前传系统处的网络拥塞，从而导致高延迟。因此，它可以对机器人、用户和云之间的无缝连接产生影响。此外，机器人可能无法在规定的时间内成功完成其目标。因此，Cloud Robotics无法处理机器人带来的流量。相反，即将到来的Fog Robotics可以通过解决Cloud Robotics的主要问题来解决问题。因此，为了检查其可行性，我们在本文中讨论了雾机器人的需求和架构。为了评估这些架构，我们使用了Fog Robotics的真实场景，并将其与Cloud Robotics进行了比较。接下来，选择延迟作为验证系统有效性的主要因素。此外，我们使用Pepper机器人，Fog机器人服务器和Cloud服务器来利用实时延迟。实验结果表明，与Cloud Robotics相比，Fog Robotics显著降低了延迟。此外，雾机器人系统的优势，挑战和未来的范围进行了进一步讨论。
英文摘要：
Human-robot interaction plays a crucial role to make robots closer to humans. Usually, robots are limited by their own capabilities. Therefore, they utilise Cloud Robotics to enhance their dexterity. Its ability includes the sharing of information such as maps, images and the processing power. This whole process involves distributing data which intend to rise enormously. New issues can arise such as bandwidth, network congestion at backhaul and fronthaul systems resulting in high latency. Thus, it can make an impact on seamless connectivity between the robots, users and the cloud. Also, a robot may not accomplish its goal successfully within a stipulated time. As a consequence, Cloud Robotics cannot be in a position to handle the traffic imposed by robots. On the contrary, impending Fog Robotics can act as a solution by solving major problems of Cloud Robotics. Therefore to check its feasibility, we discuss the need and architectures of Fog Robotics in this paper. To evaluate the architectures, we used a realistic scenario of Fog Robotics by comparing them with Cloud Robotics. Next, latency is chosen as the primary factor for validating the effectiveness of the system. Besides, we utilised real-time latency using Pepper robot, Fog robot server and the Cloud server. Experimental results show that Fog Robotics reduces latency significantly compared to Cloud Robotics. Moreover, advantages, challenges and future scope of the Fog Robotics system is further discussed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
