Flocking birds avoid collisions using visual cues and local interaction rules
Multiple studies demonstrate that flocking birds and similar animal groups rely on local interaction rules and visual cues to coordinate movement and avoid collisions.
The claim asserts that flocking birds avoid collisions using visual cues and local interaction rules. Multiple retrieved papers explicitly model and substantiate that collective motion and collision avoidance in biological swarms and flocks emerge from local interactions and visual or sensory perception of neighbors. There are no refuting papers, leading to a verdict of SUPPORTED.
Xiao Y, Lei X, Zheng Z, Xiang Y, Liu YY, Peng X. Perception of motion salience shapes the emergence of collective motions.. 2024. https://doi.org/10.1038/s41467-024-49151-x
Demonstrates that animal collective motion relies on perceiving relative motion changes and neighbors from a local, visual first-person perspective.
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David L. Krongauz, Teddy Lazebnik. Collective Evolution Learning Model for Vision-Based Collective Motion with Collision Avoidance. 2022. https://doi.org/10.1101/2022.06.09.495429
Shows that flocking and collision avoidance behaviors emerge from local interactions processed via visual and environmental inputs.
Wu W, Zhang X, Miao Y. Starling-Behavior-Inspired Flocking Control of Fixed-Wing Unmanned Aerial Vehicle Swarm in Complex Environments with Dynamic Obstacles.. 2022. https://doi.org/10.3390/biomimetics7040214
Models starling-inspired flocking and obstacle avoidance using collective patterns and local-following rules.
Zhang J, Qu Q, Chen X. Understanding collective behavior in biological systems through potential field mechanisms.. 2025. https://doi.org/10.1038/s41598-025-88440-3
Explains that collective biological behavior fundamentally emerges from local interactions among individuals responding to environmental and neighbor cues.
Kushwaha VK, Iyer P, Singh SP, Gompper G. Directional motion of a self-steering active intruder in a dense crowd of cognitive active agents.. 2026. https://doi.org/10.1038/s41598-026-52749-4
Models active agents that utilize visual perception and local directional steering rules to successfully navigate and avoid collisions.
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