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Abstract

As a result of the integration of cloud computing technologies into the field of robotics, the concept of "cloud robotics" has emerged. Unlike traditional robots, cloud-based robot systems remove computation, memory, and even some software from the local device and rely on remote resources obtained over the network. This approach ensures that robots are not limited only by their internal computing capabilities and allows them to take advantage of the wide range of opportunities offered by the cloud infrastructure. As a result, robots have access to large databases, highly parallel computing, and collective learning capabilities anytime and anywhere. In addition, cloud robotics promotes scalability by enabling the seamless addition of new robots into a network without significant hardware upgrades. It also facilitates interoperability between different robotic platforms, which enhances collaboration and standardization across industries. Furthermore, the integration of artificial intelligence with cloud resources accelerates the development of smarter, more adaptive robotic systems capable of solving complex tasks. This article analyzes the application areas and advantages of cloud-based robot systems, the classification of robot motion planning algorithms, the comparison of planning in the cloud and on the local device, technical aspects such as additional computing power, real-time, latency, and security, real-world application examples, as well as challenges and future research directions in this field based on scientific literature.

First Page

38

Last Page

45

References

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