A Minimal Model for Emergent Collective Behaviors in Autonomous Robotic Multi-Agent Systems
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911103343132672 |
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| author | Jond, Hossein B. |
| author_facet | Jond, Hossein B. |
| contents | Collective behaviors such as swarming and flocking emerge from simple, decentralized interactions in biological systems. Existing models, such as Vicsek and Cucker-Smale, lack collision avoidance, whereas the Olfati-Saber model imposes rigid formations, limiting their applicability in swarm robotics. To address these limitations, this paper proposes a minimal yet expressive model that governs agent dynamics using relative positions, velocities, and local density, modulated by two tunable parameters: the spatial offset and kinetic offset. The model achieves spatially flexible, collision-free behaviors that reflect naturalistic group dynamics. Furthermore, we extend the framework to cognitive autonomous systems, enabling energy-aware phase transitions between swarming and flocking through adaptive control parameter tuning. This cognitively inspired approach offers a robust foundation for real-world applications in multi-robot systems, particularly autonomous aerial swarms. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_08473 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Minimal Model for Emergent Collective Behaviors in Autonomous Robotic Multi-Agent Systems Jond, Hossein B. Robotics Multiagent Systems Collective behaviors such as swarming and flocking emerge from simple, decentralized interactions in biological systems. Existing models, such as Vicsek and Cucker-Smale, lack collision avoidance, whereas the Olfati-Saber model imposes rigid formations, limiting their applicability in swarm robotics. To address these limitations, this paper proposes a minimal yet expressive model that governs agent dynamics using relative positions, velocities, and local density, modulated by two tunable parameters: the spatial offset and kinetic offset. The model achieves spatially flexible, collision-free behaviors that reflect naturalistic group dynamics. Furthermore, we extend the framework to cognitive autonomous systems, enabling energy-aware phase transitions between swarming and flocking through adaptive control parameter tuning. This cognitively inspired approach offers a robust foundation for real-world applications in multi-robot systems, particularly autonomous aerial swarms. |
| title | A Minimal Model for Emergent Collective Behaviors in Autonomous Robotic Multi-Agent Systems |
| topic | Robotics Multiagent Systems |
| url | https://arxiv.org/abs/2508.08473 |