Abstract
This article focuses on typical unmanned aerial vehicle (UAV) cluster autonomous collaborative reconnaissance mission scenarios, constructs UAV classes in Matlab, and effectively constructs UAV autonomous decision-making models using two different algorithms; Using Extreme Learning Machines (ELM) and introducing neural network methods to solve autonomous decision-making problems for unmanned aerial vehicles. Test the performance of the model under multiple neural network algorithms, basically achieving unmanned aerial vehicles to complete flight targets based on multiple sensor parameters in unknown environments, using reinforcement learning algorithms to achieve autonomous decision-making of unmanned aerial vehicles, achieving multi parameter fusion (with parameters greater than 4) decision-making, with a decision-making time of less than 100ms, which can ensure timely decision-making while also considering the rationality of the model.
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
