mlsanityData to 7 Oct 2026

Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

arXiv 2402.18062 ↗First posted 28 Feb 2024cs.RO cs.AIcited by 14

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Abstract (arXiv)

With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans. However, learning and coordinating movements and actions for a large number of unmanned vehicles in complex and dynamic environments introduce significant challenges to conventional AI methods. Generative AI (GAI), with its capabilities in complex data feature extraction, transformation, and enhancement, offers great potential in solving these challenges of unmanned vehicle swarms. For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms. Specifically, we first present an overview of unmanned vehicles and unmanned vehicle swarms as well as their use cases and existing issues. Then, an in-depth background of various GAI techniques together with their capabilities in enhancing unmanned vehicle swarms are provided. After that, we present a comprehensive review on the applications and challenges of GAI in unmanned vehicle swarms with various insights and discussions. Finally, we highlight open issues of GAI in unmanned vehicle swarms and discuss potential research directions.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 65 of its 191 references that are in the map. First posted on arXiv 28 Feb 2024.

Builds on

65 of 191 references.

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Citing papers per year: 2024: 4; 2025: 10.

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  1. 2024Large Language Models for UAVs: Current State and Pathways to the Futurecited by 33
  2. 2025Generative Diffusion Models for Wireless Networks: Fundamental, Architecture, and State-of-the-Artcited by 13
  3. 2025LLM-Enabled In-Context Learning for Data Collection Scheduling in UAV-assisted Sensor Networkscited by 12
  4. 2024Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directionscited by 10
  5. 2025Next-Generation LLM for UAV: From Natural Language to Autonomous Flightcited by 10
  6. 2024Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Surveycited by 9
  7. 2025Generative AI in Transportation Planning: A Surveycited by 8
  8. 2025Generative AI for Autonomous Driving: Frontiers and Opportunitiescited by 7
  9. 2025FRSICL: LLM-Enabled In-Context Learning Flight Resource Allocation for Fresh Data Collection in UAV-Assisted Wildfire Monitoringcited by 4
  10. 2025Task Assignment and Exploration Optimization for Low Altitude UAV Rescue via Generative AI Enhanced Multi-agent Reinforcement Learningcited by 3
  11. 2024SecGenAI: Enhancing Security of Cloud-based Generative AI Applications within Australian Critical Technologies of National Interestcited by 2
  12. 2025Agentic Satellite-Augmented Low-Altitude Economy and Terrestrial Networks: A Survey on Generative Approachescited by 2
2 more
  1. 2025AIC-VDS: Attention-Based In-Context Learning for Joint Velocity Control and Data Collection Scheduling in Multi-UAV-Assisted Pipeline Monitoringcited by 1
  2. 2025Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communicationscited by 1