Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments
Abstract With the concept of "mosaic warfare," a novel combat style that involves constructing "kill webs" with unmanned aerial vehicle (UAV) swarms has emerged. However, little research has focused on this specific task scenario, particularly concerning the self-organization and...
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| Format: | Article |
| Language: | English |
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Springer
2024-11-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-024-01644-4 |
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| author | Wenlin Liu Zishuang Pan Wei Han Xichao Su Dazhao Yu Bing Wan |
| author_facet | Wenlin Liu Zishuang Pan Wei Han Xichao Su Dazhao Yu Bing Wan |
| author_sort | Wenlin Liu |
| collection | DOAJ |
| description | Abstract With the concept of "mosaic warfare," a novel combat style that involves constructing "kill webs" with unmanned aerial vehicle (UAV) swarms has emerged. However, little research has focused on this specific task scenario, particularly concerning the self-organization and adaptive collaboration of heterogeneous combat units in dynamic contested environments. Considering the scales and highly dynamic natures of such swarms, an adaptive communication network mechanism is developed based on the Molloy-Reed criterion. In contrast with common offline/noncombat task scenarios, the self-organization process is refined through agent-based modeling, and a combat effectiveness evaluation is introduced to provide enhanced task execution incentives. The proposed dynamic consensus-based coalition algorithm (DCBCA) addresses UAV intelligence defects such as "confusion," "forgetfulness," and "recklessness" during the dynamic target selection process, enabling effective bottom-up kill webs construction. Extensive simulation results demonstrate that the algorithmic system outlined in this paper can support the efficient and resilient operations of large-scale heterogeneous UAV swarms. The DCBCA outperforms the dynamically improved consensus-based grouping algorithm (CBGA) and the consensus-based timetable algorithm (CBTA) in terms of performance and convergence speed. |
| format | Article |
| id | doaj-art-0242a93e5b204ffdbeb1986338c97428 |
| institution | Kabale University |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-0242a93e5b204ffdbeb1986338c974282025-02-02T12:50:23ZengSpringerComplex & Intelligent Systems2199-45362198-60532024-11-0111112410.1007/s40747-024-01644-4Construction of kill webs with heterogeneous UAV swarms in dynamic contested environmentsWenlin Liu0Zishuang Pan1Wei Han2Xichao Su3Dazhao Yu4Bing Wan5Naval Aviation UniversityNaval Aviation UniversityNaval Aviation UniversityNaval Aviation UniversityNaval Aviation UniversityNaval Aviation UniversityAbstract With the concept of "mosaic warfare," a novel combat style that involves constructing "kill webs" with unmanned aerial vehicle (UAV) swarms has emerged. However, little research has focused on this specific task scenario, particularly concerning the self-organization and adaptive collaboration of heterogeneous combat units in dynamic contested environments. Considering the scales and highly dynamic natures of such swarms, an adaptive communication network mechanism is developed based on the Molloy-Reed criterion. In contrast with common offline/noncombat task scenarios, the self-organization process is refined through agent-based modeling, and a combat effectiveness evaluation is introduced to provide enhanced task execution incentives. The proposed dynamic consensus-based coalition algorithm (DCBCA) addresses UAV intelligence defects such as "confusion," "forgetfulness," and "recklessness" during the dynamic target selection process, enabling effective bottom-up kill webs construction. Extensive simulation results demonstrate that the algorithmic system outlined in this paper can support the efficient and resilient operations of large-scale heterogeneous UAV swarms. The DCBCA outperforms the dynamically improved consensus-based grouping algorithm (CBGA) and the consensus-based timetable algorithm (CBTA) in terms of performance and convergence speed.https://doi.org/10.1007/s40747-024-01644-4Heterogeneous unmanned aerial vehicle swarmKill webs constructionComplex adaptive systemsDynamic adaptive networksResilience |
| spellingShingle | Wenlin Liu Zishuang Pan Wei Han Xichao Su Dazhao Yu Bing Wan Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments Complex & Intelligent Systems Heterogeneous unmanned aerial vehicle swarm Kill webs construction Complex adaptive systems Dynamic adaptive networks Resilience |
| title | Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments |
| title_full | Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments |
| title_fullStr | Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments |
| title_full_unstemmed | Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments |
| title_short | Construction of kill webs with heterogeneous UAV swarms in dynamic contested environments |
| title_sort | construction of kill webs with heterogeneous uav swarms in dynamic contested environments |
| topic | Heterogeneous unmanned aerial vehicle swarm Kill webs construction Complex adaptive systems Dynamic adaptive networks Resilience |
| url | https://doi.org/10.1007/s40747-024-01644-4 |
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