In order to adapt to the changes in the states of moving targets and meet the requirements of quality of service in communication among unmanned aerial vehicles (UAVs), the UAVs formation needs to dynamically adjust t...In order to adapt to the changes in the states of moving targets and meet the requirements of quality of service in communication among unmanned aerial vehicles (UAVs), the UAVs formation needs to dynamically adjust tracking tasks and tracking paths, when they carry out a mission of tracking multiple moving targets. A multi-targets tracking algorithm based on task allocation consensus is proposed for UAVs to track multiple moving targets under the distributed control architecture in the limited communication range. This algorithm creates a distributed dynamic task allocation model using intermittent asynchronous communication principle to realize the sharing of observation information gathered by each UAV with fewer communications. In addition, this algorithm also makes it possible that multi-UAVs can plan tracking paths for multiple moving targets. We implement the algorithm on the formation with three UAVs to track three moving targets through simulation. Simulation results show the effectiveness of the proposed algorithm. ? 2016 Beijing Institute of Aerospace Information.展开更多
基金supported by the International S&T Cooperation Projects of China(2015DFR10510)the National Natural Science Foundation of China(61440048+1 种基金61562018)the Scientific Research Program of the Higher Education Institutions of Hainan Province(HNKY2014-04)
文摘In order to adapt to the changes in the states of moving targets and meet the requirements of quality of service in communication among unmanned aerial vehicles (UAVs), the UAVs formation needs to dynamically adjust tracking tasks and tracking paths, when they carry out a mission of tracking multiple moving targets. A multi-targets tracking algorithm based on task allocation consensus is proposed for UAVs to track multiple moving targets under the distributed control architecture in the limited communication range. This algorithm creates a distributed dynamic task allocation model using intermittent asynchronous communication principle to realize the sharing of observation information gathered by each UAV with fewer communications. In addition, this algorithm also makes it possible that multi-UAVs can plan tracking paths for multiple moving targets. We implement the algorithm on the formation with three UAVs to track three moving targets through simulation. Simulation results show the effectiveness of the proposed algorithm. ? 2016 Beijing Institute of Aerospace Information.
