Collaborative Search and Package Delivery Strategy for UAV Swarms Under Area Restrictions

• Published in: Journal of advanced computational intelligence and intelligent informatics Vol. 27; no. 5; pp. 932 - 941
• Main Authors: Xin, Ziwei, Li, Juan, Li, Jie, Liu, Chang
• Format: Journal Article
• Language: English
• Published: Tokyo Fuji Technology Press Co. Ltd 01.09.2023
• Subjects: Adaptability; Algorithms; Collaboration; Control algorithms; Decision making; Decoupling; Efficiency; Flow simulation; Methods; Path predictors; Planning; Searching; Simulation; Unmanned aerial vehicles
• ISSN: 1343-0130; 1883-8014
• DOI: 10.20965/jaciii.2023.p0932

The rapid implementation of multi-task decoupling in restricted flight areas for unmanned aerial vehicle swarms is crucial to ensure swarm effectiveness. This study introduces a task-switching mechanism in the bio-inspired rule-based (Bio-RB) decision-making algorithm and establishes a mapping relationship from behavioral rules to task modes. A complete decision model is constructed for the cooperative search and package delivery tasks. To further improve the search efficiency of swarms in restricted areas, a boundary-handling strategy based on the combination of path prediction and virtual agents is proposed. The overall scheme is termed the task-driven rule-based (Task-RB) decision-making algorithm. The proposed Task-RB method is evaluated under full-flow simulation. Numerical experiments demonstrate the superior performance of the proposed Task-RB method against the Bio-RB method under different instances.