Cloud robotics is currently regarded as one of the cutting-edge research areas within the mainstream automation and artificial intelligence fields. The new machine-to-cloud communication will increase the productivity and efficiency of industrial robots. For decades, automated devices have been developing and affecting practically every element of life. Cloud computing and associated technologies have a great deal of potential to get around hardware limitations and boost performance. This study emphasises the developments in robotic technology with a particular focus on cloud-based automation as a new development. Unexpected effects of robotic technologies on human life have been seen. This chapter discusses the fundamental ideas, the creation process, and the general architecture of cloud robotics in order to explore the potential of clouds for improving robotics for industrial systems. Finally, it examines how useful cloud robotic systems might be in various real-world scenarios.
Top1. Introduction
The improvement in the development of robots has rapidly increased in the industries, and the result causes the machines to become configured to reach a improved level of efficiency with features such as good accuracy, robustness and good compatability. Robotic automation provides a crucial role in executing the everyday tasks which are carried out on a regular basis. Robots are used to construct a network known as a cluster of robots, where each robot serves as point of data, and the robots are connected by wireless or wired communication (Herm et al., 2023). To do tasks more efficiently, the cloud robots are outfitted with making decisions and number-sensing components.
Over the past few decades, robotics has undergone significant advancements, leading to an increase in the applications of this technology to a variety of real-world issues, such as automated manufacturing, extraterrestrial operations, unsupervised operations the catastrophe devices, self-movable cars, socially aligned robots, and medical care and other specific featured robots. The main intention of upon-board hardware and computational limitations of the single robots utilized in many of these applications place restrictions on their capabilities. The area of network robotics first evolved approximately two decades ago to address this issue, connecting group of robots using secured as well wired or unsecured network (Udendhran et al., 2023). By exchanging perceived data and doing tasks collaboratively and/or in unison, networked robots solve the issue with isolated robot systems. Network enabled robots, however, would experience many issues as one hand robot systems.
Resource restrictions, communication information as well other learning constraints, and communication limits are the key issues with networked robots. The compute and storage capabilities of each robot are constrained by its technology, which has implications for collective robots connected across a network (Dittakavi, 2022). Once a robot has been conceived, constructed, and put into service, it is technically challenging to update or change available device configurations. Robots connected over a network are likewise restricted by information because they can only access the collected data using other robots with similar sensors and a similar network (Vermesan et al., 2022). This can usually result in improved performance in static settings; nevertheless, their performance rapidly deteriorates when the environment abruptly changes or if they are placed in unusual circumstances.
The combination of robotics and automation with cloud computing in recent times has surfaced as a revolutionary concept, radically altering the functionalities and capacities of conventional robotic systems. This thorough analysis explores the ever-changing topic of cloud automation and robotics, including information on methods, classification, uses, and future directions for the field. Robotics systems can overcome the constraints of onboard computing power and memory by utilising the enormous computing and storage capacities of the cloud, providing improved sensing, cognition, and decision-making abilities. This paper classifies several cloud robotics systems and methodologies, such as internet-based control, data storage, compute offloading, and collaborative learning, using a systematic taxonomy.
It also highlights the revolutionary power of cloud-enabled robots across domains by examining a wide range of industries spanning manufacturing, healthcare, the agricultural sector, disaster response, and beyond. Notwithstanding the encouraging progress, a number of research obstacles still exist, encompassing security and privacy apprehensions, latency problems, and scale constraints. Through the resolution of these issues, scientists may fully realise the endless possibilities of cloud robotics, opening the door to the creation of robotic systems that are scalable, intelligent, and adaptable to a variety of real-world situations. This study promotes creativity and advances this quickly developing subject by providing a fundamental resource for academics, professionals, and hobbyists attempting to negotiate the challenging terrain of cloud robots and automation.