Dynamic Discrete Pigeon-Inspired Optimization for Multi-UAV Cooperative Search-Attack Mission Planning

• Published in: IEEE transactions on aerospace and electronic systems Vol. 57; no. 1; pp. 706 - 720
• Main Authors: Duan, Haibin, Zhao, Jianxia, Deng, Yimin, Shi, Yuhui, Ding, Xilun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; B spline functions; Dynamic discrete pigeon-inspired optimization (D<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> 2</tex-math> </inline-formula> </named-content>PIO); Heuristic algorithms; Mission planning; Optimization; path planning; Planning; Search problems; Searching; Solid modeling; Strategy; Task analysis; unmanned aerial vehicle (UAV); Unmanned aerial vehicles; Visualization; visualization simulation; Waypoints
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2020.3029624

For multiple unmanned aerial vehicles (UAVs) performing aerial search-attack tasks, there is a tradeoff between maximizing total benefit and minimizing consumption under the validity of constraints. This article proposes a dynamic discrete pigeon-inspired optimization algorithm to handle cooperative search-attack mission planning for UAVs, which integrates the centralized task assignment and distributed path generation aspects of the problem. Besides, a solution acceptance strategy is proposed to avoid frequent task switching. To design a reasonable objective function, the probability map is constructed and updated by Bayes formula to guide the following search motion, and a response threshold sigmoid model is adopted for target allocation during executing attack. Moreover, the flyable trajectories are generated by B-spline curves based on the simplified waypoints. Finally, numerical experiments prove that the proposed methods can provide feasible solutions for multiple UAVs considering different scenarios, such as the absence or presence of threats and insufficient resources. The results also show that the solution acceptance strategy is effective to improve performance. Moreover, the extensible mission planning system also integrates with an interactive 3D visualization simulation module, where the multi-UAV coordinated flight processes are demonstrated dynamically.