Emergent Multi-View Fidelity in Autonomous UAV Swarm Sport Injury Detection
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912829629530112 |
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| author | Cheng, Yu Šiljak, Harun |
| author_facet | Cheng, Yu Šiljak, Harun |
| contents | Accurate, real-time collision detection is essential for ensuring player safety and effective refereeing in high-contact sports such as rugby, particularly given the severe risks associated with traumatic brain injuries (TBI). Traditional collision-monitoring methods employing fixed cameras or wearable sensors face limitations in visibility, coverage, and responsiveness. Previously, we introduced a framework using unmanned aerial vehicles (UAVs) for monitoring and real time kinematics extraction from videos of collision events. In this paper, we show that the strategies operating on the objective of ensuring at least one UAV captures every incident on the pitch have an emergent property of fulfilling a stronger key condition for successful kinematics extraction. Namely, they ensure that almost all collisions are captured by multiple drones, establishing multi-view fidelity and redundancy, while not requiring any drone-to-drone communication. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_06588 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Emergent Multi-View Fidelity in Autonomous UAV Swarm Sport Injury Detection Cheng, Yu Šiljak, Harun Robotics Multiagent Systems Systems and Control Adaptation and Self-Organizing Systems Accurate, real-time collision detection is essential for ensuring player safety and effective refereeing in high-contact sports such as rugby, particularly given the severe risks associated with traumatic brain injuries (TBI). Traditional collision-monitoring methods employing fixed cameras or wearable sensors face limitations in visibility, coverage, and responsiveness. Previously, we introduced a framework using unmanned aerial vehicles (UAVs) for monitoring and real time kinematics extraction from videos of collision events. In this paper, we show that the strategies operating on the objective of ensuring at least one UAV captures every incident on the pitch have an emergent property of fulfilling a stronger key condition for successful kinematics extraction. Namely, they ensure that almost all collisions are captured by multiple drones, establishing multi-view fidelity and redundancy, while not requiring any drone-to-drone communication. |
| title | Emergent Multi-View Fidelity in Autonomous UAV Swarm Sport Injury Detection |
| topic | Robotics Multiagent Systems Systems and Control Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2505.06588 |