Affiliation:
1. School of Automation, Beijing Institute of Technology, Beijing 100081, China
2. Jiangsu Automation Research Institute, Lianyungang 222000, China
3. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Abstract
This paper addresses task allocation to multi-UAV systems in time- and communication-constrained environments by presenting an extension to the novel heuristic performance impact (PI) algorithm. The presented algorithm, termed local reassignment performance impact (LR-PI), consists of an improved task inclusion phase, a novel communication and conflict resolution phase, and a systematic method of reassignment for unallocated tasks. Considering the cooperation in accomplishing tasks that may require multiple UAVs or an individual UAV, the task inclusion phase can build the ordered task list on each UAV with a greedy approach, and the significance value of tasks can be further decreased and conflict-free assignments can be reached eventually. Furthermore, the local reassignment for unallocated tasks focuses on maximizing the number of allocated tasks without conflicts. In particular, the non-ideal communication factors, such as bit error, time delay, and package loss, are integrated with task allocation in the conflict resolution phase, which inevitably exist and can degrade task allocation performance in realistic communication environments. Finally, we show the performance of the proposed algorithm under different communication parameters and verify the superiority in comparison with the PI-MaxAsses and the baseline PI algorithm.
Reference26 articles.
1. A Consensus-Based Grouping Algorithm for Multi-agent Cooperative Task Allocation with Complex Requirements;Hunt;Cogn. Comput.,2014
2. TRMaxAlloc: Maximum task allocation using reassignment algorithm in multi-UAV system;Qamar;Comput. Commun.,2023
3. Wang, J., Duan, S., Ju, S., Lu, S., and Jin, Y. (2022). Evolutionary task allocation and cooperative control of unmanned aerial vehicles in air combat applications. Robotics, 11.
4. A heuristic distributed task allocation method for multivehicle multitask problems and its application to search and rescue scenario;Zhao;IEEE Trans. Cybern.,2015
5. Multi-criterion multi-UAV task allocation under dynamic conditions;Qamar;J. King Saud Univ.-Comput. Inf. Sci.,2023