Abstract
This paper presents an application of Boolean networks-based auction algorithm (BNAA) for task assignment in unmanned aerial vehicles (UAVs) systems. Under reasonable assumptions, the assignment framework consists of mission control system, communication network, and ground control station. As the improved algorithm of consensus-based bundle algorithm (CBBA), the BNAA utilizes a cluster-based combinatorial auction policy to handle multiple tasks. Instead of empirical method based on look-up table about conditional variables, Boolean network is introduced into consensus routine of BNAA for solving the conflict of assignment across the fleet of UAVs. As a new mathematic theory, semitensor product provides the implementation and theoretical proof of Boolean networks. Numerical results demonstrate the effectiveness and efficiency of proposed BNAA method.
Highlights
In the last decade, the unmanned aerial vehicles (UAVs) are developed into collaborative applications [1], such as search and destroy mission, persistent surveillance, border or perimeter patrol [2], and tracking and rescue mission [3]
This paper presents an application of Boolean networks-based auction algorithm (BNAA) for task assignment in unmanned aerial vehicles (UAVs) systems
The assignment architecture of UAVs addresses an integrated cooperating platform with the ability to perform the task assignment adhering to a mission control systems (MCS), for running collaborative and assignment algorithm
Summary
The unmanned aerial vehicles (UAVs) are developed into collaborative applications [1], such as search and destroy mission, persistent surveillance, border or perimeter patrol [2], and tracking and rescue mission [3]. The consensus phase is addressed to solve the conflict of assignment between the UAVs. The consensus algorithm of CBBA achieves by look-up table approach. The consensus algorithm of CBBA achieves by look-up table approach It is essentially empirical method, the original and extended CBBA methods can achieve the convergence to conflict-free assignment [14,15,16]. Considering the efficiency of the computation and communication, this paper presents a Boolean networks-based auction algorithm (BNAA). As similar structure of CBBA, there are two phases for BNAA: combinatorial auction and Boolean networks-based consensus. As the first phase has dealt with the combinatorial assignment, the second phase of BNAA is in charge to handle the conflicts of assignment In this process, the Boolean networks method is introduced to model the consensus algorithm of look-up table about conditional variables.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
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 call
