Abstract
This paper addresses the dynamic allocation of strongly coupled multiple tasks in cooperative decision and control of a distributed autonomous UAV team. Many techniques can be used for single task assignment, but multiple task assignment requires the enforcement of a rigid set of timing and precedence constraints. This is computationally intensive if there are many tasks. This paper discusses the methods of relative benefit, iterative network flow, and iterative auction for multiple assignment. These approaches are computationally efficient for on-line computation and can satisfy the task timing constraints. Simulations are performed for a team of eight vehicles cooperatively searching for and attacking targets. Results show that multiple assignment using these techniques results in a significant improvement in performance over single task assignment.
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.
