Publication Details
Abstract
With the advancement of modern technology, networks of autonomous vehicles UI and interconnected cooperative rotary robots face various challenges in control and navigation operations. To achieve optimal performance and the highest efficiency in the operation of these networks, control and coordination must be in real-time, especially in applications that require large numbers and crowded models. In this study, a model is developed to predict the movement of networks of autonomous vehicles and interconnected cooperative rotary robots in order to facilitate their movement under changing working conditions. The technique of the proposed model relies on providing a distributed controller that operates on a specified time to manage the control of autonomous vehicles and rotary robots and achieve high performance efficiency. In addition to offering workable answers to real-time coordination issues in unmanned aerial vehicle and rotorcraft collaboration networks, this suggested architecture offers notable advancements in distributed computing methodologies. To run the network effectively and dynamically, multi-agent technology is used. This entails choosing suitable routes, figuring out locations, and taking temporal and spatial network performance limits into account. Additionally, this research advances the practical application of autonomous vehicle performance, particularly in applications requiring high network stability and precise coordination.