In the face of the development of robotic technology, integration with cloud technologies is a big opportunity to greatly improve robots. This chapter will synthetize the spirit which robotic applications lacks to refine and add depth to it. Also, this procedure not only gives the robotic device more computing power, but also ups its storage capacities and resource management, all without rendering robotical atrophy. In this chapter, the authors examine several different forms of application running away from home. In particular, with the growing public interest in robotics, it is vital that not only participants from industry but also researchers and developers who should realize that through cloud-based offloading they really have a chance to create a revolution.
Top1. Introduction
Recently, with the advent of cloud computing, robotics and this new branch known as “cloud robots” has been creating ripples. For example, seamless combining of cloud computing technologies with robotic devices represents a completely different kind of concept that jointly integrates aptitudes, connection and collaboration in ways which have never been seen before (Kumar and R. Singhal 202 2). In this chapter, we will briefly introduce cloud robotics in general and then discuss the development of some basic concepts such as application offloading together.
Definition of Cloud Robotics: In essence, cloud robotics is synonymous with the union of robotic systems and cloud computing infrastructure. With this paradigm, robots access cloud-based computation and data storage resources as well as deep learning algorithms to improve their own capabilities (Nayyar J., A. Nagpal), 2018). Unlike robot-only robots, cloud connected robots can access and process prodigious amounts of information in real life. They are the only way to make better informed decisions about what to do and perform complicated tasks more rapidly (P. S. Kumar and A. Sharma, 2019).
The addition of cloud technologies extends the reach of robotic systems beyond the constraints of onboard computing. In exploiting the cloud, robots have access to a seemingly inexhaustible supply of computational power, can rapidly reference huge amounts of data and information and can make use of some powerful machine-learning algorithms (S. El-Gendy, 2020). In this form of symbiosis between robots and the cloud, robotic systems have reached a state where they can adapt, learn and progress over time. Their evolution is no longer limited by their onboard hardware.
Importance of Cloud Robotics: Cloud robotics allows robots to be elevated in ability, becoming intelligent entities capable of complicated operations. This is the real significance of cloud robotics. One of the main benefits is that it makes real-time data processing possible (K. N. V. Srinivas and P. K. Lakineni, 2023). Unlike traditional robots which merely relied on local computing, cloud-based robots can delegate compute-intensive tasks to remote servers, saving time and enhancing the analysis of data streams.
Figure 1.
Schematic representation of a cloud robotic system, emphasizing robot connections to cloud computing through wireless network
A Cloud Robotic System (Figure. 1) is presented schematically here, with robots and cloud computing linked via a wireless network (P. S. Kumar, S. Gangadharan and S. C. N, 2023). You will find in this pictorial representation all manner of parts, including robotic objects and cloud servers, linked by lines or arrows to represent the movement of information. The cloud may be representative of the wireless network, suggesting the link between robotic systems and the cloud (Hussain, N., Samal, A., 2024). To diagram the underlying concept, this figure depicts how robots hand data and computational duties among themselves to outside resources in cloud computing via their wireless communications--the very activity that constitutes what we call cloud robotics. Furthermore the advent of cloud robotics has encouraged integration of robotic systems. Through the interconnectivity cloud networks, robots are able to exchange information as well know-hows or delegating tasks (V. S. Prasad, Y Mahajan and SuneethaS., 2023). This kind of collaborative ability becomes very useful for situations requiring robots to work together in, say, industrial automation or a search-and-rescue mission.